Yann Neuhaus

This blog post is focused at developers and software architects. I’m probably not writing at the right place. You’re on an infrastructure experts blog and the author is an Oracle DBA. So what can you learn from someone working on that 30 years old technology talking about that old SQL language ? You run with modern languages, powerful frameworks, multi-layer architecture, micro-services, distributed database and of course all open-source. You hate your DBA because he is the major slow-down for your agile development. You don’t want SQL. You don’t want databases. You don’t want DBA.

How can I encourage you to read this blog post? I was not always an DBA. I started as a developer, more than 20 years ago. And believe me, it was not prehistory at all. Object-Oriented design, Rapid Application Development, Automatic programming (remember C.A.S.E.?), visual programming (have you ever seen an IDE like IBM Visual Age?), query generation (early days of Business-Objects). All these evolved with more and more languages, frameworks, layers, micro-services, XML, SOA, JSON, REST,… but only one technology remained: the critial persistent data is still in a relational database and accessed by SQL.

What is a database

Most of developers think that a database is there to store and retrieve data. I’m sorry but that’s wrong. That may have been right a long time ago, with key-value storage and hierarchical databases, but that’s too old for me. When I started to work, databases were already doing far more than that. Let me explain. With those prehistoric databases, you retrieved data in the same way you stored it. You insert with a key, you fetch with that key. It is easy to explain to modern developers because they “invented” it few years ago, calling it CRUD (Create Read Update Delete). First argument of those CRUD methods is a key value. And you store unformatted data as XML or JSON associated to that value. If this is the only feature that you need, then for sure you don’t want a database.

Relational database management systems (RDBMS) are doing a lot more than that. First, you can query data in a completely different way than you inserted it. And this is the real life-cycle of data. For example, You take orders, one by one, with customer and product information for each of them. Of course you can update and read it with the order ID that has been generated, but that’s only a small use case and probably not the most critical. Warehouse users will query (and update) orders by product. Delivery users will query (and update) orders by customer. Marketing users will query by channels and many other dimensions. Finance will join with accounting. With a persistence only system, you have to code all that. Of course if you declared the mapping of associations, you can navigate through them. But the user requirement is to get a set of orders, or a quantity of products in stock, or a subset of customers, which is different from navigating through orders one by one. With a database, you dont need to code anything. With a proper data model what you inserted can be manipulated without its key value. All data that you have inserted can be accessed from any different point of view. And you don’t have to code anything for that. Imagine a Data Access Object with ‘QueryBy methods covering any combination of columns and operators.

A database system does not only store data, it processes data and provide a service to manipulate data.

SQL

SQL is not a language to code how to get the information. SQL only describes what you want. It’s a question you ask to a data service. Same idea as Uber where you enter your destination and desired car and the service manages everything for you: the path, the communication, the paiement, the security. You may not like the SQL syntax, but it can be generated. I’m not talking about generating CRUD statements here, but generating SQL syntax from a SQL semantic expressed in Java or example. There’s a very good example for that: jOOQ (look at the exemples there).

I understand that you can hate SQL for it’s syntax. SQL was build for pre-compilers, not for execution time parsing of text, and I’ll come back on that later with static SQL. But you can’t say that SQL semantic is not modern. It’s a 4th generation language that saves all the procedural coding you have to do with 3rd generation languages. SQL is a declarative language build on a mathematics theory. It goes far beyond the for() loops and if()else.

In SQL you describe the result that you want. How to retrieve the data is done by the database system. The optimizer builds the procedural code (know as the execution plan) and the execution engine takes care of everything (concurrency, maintaining redundant structures for performance, caching, multithreading, monitoring, debugging, etc). Do you really want to code all that or do you prefer to rely on a data service that does everything for you?

You know why developers don’t like SQL? Because SQL has not been designed for programmers. It was for users. The goal was that a non-programmer can ask its question to the system (such as “give me the country of the top customers having bought a specific product in last 3 months”) without the need of a developer. There was no GUI at that time, only Command Line Interface, and SQL was the User Friendly Interface to the database. Today we have GUIs and we don’t need SQL. But it is there so programmers build tools or framework to generate SQL from a programming language. Sure it is ridiculous and it would be better to have a programming language that directly calls the SQL semantic without generating plain old English text. We need a Structured Query Language (SQL) we just don’t need it to be in English.

Set vs loops

So why do people prefer to code everything in procedural language (3GL)? Because this is only what they learned. If at school you learned only loops and comparisons, then you are going to access data in loops. If you learned to think about data as sets, then you don’t need loops. Unfortunately, the set concepts are teached in mathematics classes but not in IT.

Imagine you have to print “Hello World” 5 times. Which pseudo-code so you prefer?


print("Hello World\n")
print("Hello World\n")
print("Hello World\n")
print("Hello World\n")
print("Hello World\n")


or


print ( "Hello World\n" + "Hello World\n" + "Hello World\n" + "Hello World\n" + "Hello World\n" )


I’ve put that in pseudo-code. I don’t want to play with String and StringBuffer here. But the idea is only to explain that if you have to process a set of things it is more efficient to process them as a set rather than one-by-one. That works for everything. And this is where databases rocks: they process sets of rows. If you have to increment the column N by one in every row of your table T, you don’t need to start a loop and increment the column row-by-row. Just ask your RDBMS data service to do it: ‘/* PLEASE */ UPDATE T set N=N+1′. The “please” is in comment because everything that is not there to describe the result is not part of SQL. You have to use hints to force the way to do it, but they are written as comments because SQL do not allow any way to tell how to do it. This was a joke of course, the “please” is not mandatory because we are talking to a machine.

ACID

I’m not sure you get all the magic that is behind:

UPDATE T set N=N+1;


it’s not a simple loop as:

for each row in T
set N=N+1


The RDBMS does more than that. Imagine that there is a unique index on the column N. How many lines of code do you need to do that N=N+1 row by row and be sure that at any point you don’t have duplicates? Imagine that after updating half of the rows you encounter someone else currently updating the same row. You have to wait for his commit. But then, if he updated the value of N, do you increment the past value or the new one? You can’t increment the old one or his modification will be lost. But if you increment the new one, your previous incremented rows are inconsistent because they were based on a previous state of data.
I was talking about having an index. You have to maintain this index as well. You have to be sure that what is in cache is consistent with what is in disk. That modifications made in the cache will not be lost in case of server failure. And if you run in a cluster, those caches must be synchronized.

Coding the same as this “UPDATE T set N=N+1″ in a procedural language is not easy and can become very complex in a multi-user environment.

Maybe you have all the tools you need to generate that code. But if you code it you have to test it. Are your tests covering all concurrency cases (sessions updating or reading same rows, or different rows from same table,…). What is already coded within the database has already been tested. It’s a service and you just have to use it.

Static SQL

I claimed above that SQL is there to be pre-compiled. Yes, SQL is witten in plain text, like most of programming languages, and must be parsed, optimized, compiled. It’s not only for performance. The main reason is that you prefer to get errors at compile time than at runtime. If you put SQL in text strings in your code it will remain text until execution time when it will be prepared. And only then you will get errors. The second reason is that when the SQL is parsed, it is easy to find the dependencies. Want to see all SQL statements touching to a specific column? Do you prefer to do guess on some text search or to methodically follow dependencies?

Yes, SQL is there to be static and not dynamic. That claim may look strange for an Oracle DBA because all statements are dynamic in Oracle. Even at the time of precompilers (such as Pro*C) the statements were parsed but were put as text in the binary. And at first execution, they are parsed again and optimized. If you want the execution plan to be defined at deployment time, you have to use Outlines or SQL Plan Baselines. There is no direct way to bind the execution plan at deployment time in Oracle. In my opinion the static SQL as it is known on DB2 for example is really missing in Oracle. OLTP Software Vendors would love to ship the optimized execution plans with their application. Imagine that all SQL statements in an OLTP application are parsed and optimized, compiled as bound procedures, similar to stored procedures, with procedural access (the execution plan) and you just have to call them. For reporting, DSS, BI you need the plans to adapt to the values and volume of data, but for OLTP you need stability. And from the application, you just call those static SQL like a data service.

Talking about procedural execution stored in the database, I’m coming to stored procedures and PL/SQL of course.

Stored Procedures

When you code in your 3GL language, do you have functions that update global variables (BASIC is the first language I learned and this was the idea) or do you define classes which encapsulate the function and the data definition? The revolution of Object Oriented concepts was to put data and logic at the same place. It’s better for code maintainability with direct dependency procedural code and data structures. It’s better for security because data is accessible only through provided methods. And it’s better for performance because procedural code access data at the same place.

Yes Object Oriented design rocks and this why you need to put business logic in the database. Putting the data on one component and running the code on another component of an information system is the worst you can do. Exactly as if in your Object Oriented application you store the object attributes on one node and run the methods on another one. And this is exactly what you do with the business logic outside of the database. Your DAO objects do not hold the data. The database does. Your objects can hold only a copy of the data, but the master copy where are managed concurrency management, high availability and persistance is in the database.

We will talk about the language later, this is only about the fact that the procedural code run in the same machine and the same processes than the data access.
There are a lot of myths about running business logic in the database. Most of them come from ignorance. Until last Monday I believed that one argument against running business logic in the database was unbeatable: You pay Oracle licences on the number of CPU, so you don’t want to use the database CPUs to run something that can run on a free server. I agreed with that without testing it, and this is where myths come from.

But Toon Koppelaars has tested it and he proved that you use more database CPU when you put the business logic outside of the database. I hope his presentation from Oak Table World 2016 will be available soon. He proved that by analyzing exactly what is running in the database, using linux perf and flame graphs: https://twitter.com/ChrisAntognini/status/778273744242352128

All those rountrips from remote compute server, all those row-by-row processing coming from that design have an higher footprint on the database CPUs that directly running the same on the database server.

PL/SQL

Running business logic on the database server can be done with any language. You can create stored procedures in Java. You can code external procedures in C. But those languages have not been designed for data manipulation. It is sufficient to call SQL statements but not when you need procedural data access. PL/SQL is a language made for data processing. It’s not only for stored procedure. But it’s the only language that is coupled with your data structure. As I said above, it’s better to think in sets with SQL. But it may be sometimes complex. With PL/SQL you have a procedural language which is intermediate between row-by-row and sets because it has some bulk processing capabilities.

In pseudo-code the Hello World above is something like that:


forall s in ["Hello World\n","Hello World\n","Hello World\n","Hello World\n","Hello World\n"] print(s)


It looks like a loop but it is not. The whole array is passed to the print() function and loop is done at lower level.

In PL/SQL you can also use pipeline functions where rows are processed with a procedural language but as a data stream (like SQL does) rather than loops and calls.

I’ll go to other advantages of PL/SQL stored procedures but here again there is one reason frequently raised to refuse PL/SQL. You can find more developers in .Net or Java than in PL/SQL. And because they are rare, they are more expensive. But there is a counter argument I heard this week at Oracle Open World (but I don’t remember who raised that point unfortunately). PL/SQL is easy to learn. Really easy. You have begin – exception – end blocks, you declare all variables, you can be modular with procedures and inline procedures, you separate signature and body, you have very good IDE, excellent debugger and easy profiler,… and you can run it on Oracle XE which is free. So, if you have a good Java developer he can write efficient PL/SQL in a few days. By good developer, I mean someone who understands multi-user concurrency problems, bulk processing, multi-threading, etc.

There are less PL/SQL developers than Java developers because you don’t use PL/SQL. It’s not the opposite. If you use PL/SQL you will find developers and there are many software vendors that code their application in PL/SQL. Of course PL/SQL is not free (except in Oracle XE) but it runs on all platforms and on all editions.

Continuous Integration and Deployment, dependency and versioning

I come back quickly to the advantages of using a language that is coupled with your data.

PL/SQL stored procedures are compiled and all dependencies are stored. With one query on DBA_DEPENDENCIES you can know which tables your procedure is using and which procedures use a specific table. If you change the data model, the procedures that have to be changed are immediately invalidated. I don’t know any other language that does that. You don’t want to break the continuous integration build every time you change something in a table structure? Then go to PL/SQL.

Let’s go beyond continuous integration. How do you manage database changes in continuous deployment? Do you know that with PL/SQL you can modify your data model online, with your application running and without breaking anything? I said above that procedures impacted by the change are invalidated and the must be adapted to be able to be compiled. But this is only for the new version. You can deploy a new version of those procedures while the previous version is running. You can test this new version and only when everything is ok you switch the application to the new version. The feature is called Edition Based Redefinition (EBR) it exists since 11g in all Oracle editions. It’s not known and used enough, but all people I know that use it are very happy with it.

In development environment and continuous integration, it is common to say that the database always cause problem. Yes it is true but it’s not inherent to the database but the data. Data is shared and durable and this is what makes it complex. The code can be deployed in different places, and can be re-deployed if lost. Data can be updated at only one place and visible to all users. Upgrading to a new version of application is easy: you stop the old version and start the new version. For data it is different: you cannot start from scratch and you must keep and upgrade the previous data.

Object-Relational impedance

I’m probably going too far in this blog post but the fact that data is shared and durable is the main reason why we cannot apply same concepts to data objects (business objects) and presentation objects (GUI components). Application objects are transient. When you restart the application, you create other objects. The identity of those objects is an address in memory: it’s different on other systems and it’s different once application is restarted. Business objects are different. When you manipulate a business entity, it must have the same identity for any users, and this identity do not change when application is restarted, not even when application is upgraded. All other points given as “object-relational impedance” are minor. But the sharing and durability of business object identity is the reason why you have to think differently.

Where to put business logic?

If you’re still there, you’ve probably understood that it makes sense to run the data logic in the database, with declarative SQL or procedural PL/SQL stored procedures, working in sets or at least in bulk, and with static SQL as much as possible, and versioned by EBR.

Where to put business logic then? Well, business logic is data logic for most of it. But you’ve always learned that business logic must be in the application tier. Rather than taking reasons given one by one and explain what’s wrong with them, let me tell you how came this idea of business logic outside of the database. The idea came from my generation: the awesome idea of client/server.

At first, data was processed on the servers and only the presentation layer was on the user side (for example ISAM was very similar with what we do with thin web pages). And this worked very well, but it was only green text terminals. Then came PCs and Windows 3.11 and we wanted graphical applications. So we built applications on our PCs. But that was so easy that we implemented all business logic there. Not because it’s a better architecture, but because anyone can build his application without asking to the sysops. This was heaven for developers and a nightmare for operations to deploy those applications on all the enterprise PCs.
But this is where offloading business logic started. Application written with nice IDEs (I did this with Borland Paradox and Delphi) connecting directly to the database with SQL. Because application was de-correlated from the database everything was possible. We even wanted to have applications agnostic of the database, running in any RDBMS. Using standard SQL and standard ODBC. Even better: full flexibility for the developer by using only one table with Entity-Value-Attribute.

Actually, the worst design anti-patterns have been invented at that time and we still see them in current applications – totally unscalable.

When finally the deployment of those client/server applications became a nightmare, and because internet was coming with http, html, java, etc. we went to 3-tier design. Unfortunately, the business logic remained offloaded in the application server instead of being part again of the database server.

I mentioned ODBC and it was another contributor to that confusion. ODBC looks like a logical separation of the application layer and the database layer. But that’s wrong. ODBC is not a protocol. ODBC is an API. ODBC do not offer a service: it is a driver running on both layers and that magically communicates through network: code to process data on one side and data begin on the other.

A real data service encapsulates many SQL statements and some procedural code. And it is exactly the purpose of stored procedures. This is how all data applications were designed before that client/server orgy and this is how they should be designed today when we focus on centralization and as micro-services applications.

So what?

This blog post is already too long. It comes from 20 years experience as developer, application DBA, and operation DBA. I decided to write this when coming back from the Oracle Open World where several people are still advocating for the right design, especially Toon Koppelaars about Thick Database at Oak Table World and the amazing panel about “Thinking clearly about application architecture” with Toon Koppelaars, Bryn Llewellyn, Gerald Venzl, Cary Millsap, Connor McDonald

The dream of every software architect should be to attend that panel w/ @ToonKoppelaars @BrynLite @GeraldVenzl @CaryMillsap @connor_mc_d pic.twitter.com/npLzpnktMK

— Franck Pachot (@FranckPachot) September 22, 2016

Beside the marketing stuff, I was really impressed by the technical content around the Oracle Database this year at OOW16.

 

Cet article Modern software architecture – what is a database? est apparu en premier sur Blog dbi services.

At the end of Oracle Open World my last BLOG concerning OOW 2016 covering day 4 and 5:

Wednesday is the day of the Party: Oracle’s appreciation event, a concert with Gwen Stefani and Sting at the AT&T Park (Stadium of the San Francisco Baseball team, the Giants). It was a great event with awesome musicians.

Before the party I visited the session “Oracle Active Data Guard: Power, Speed, Ease and Protection” provided by Larry M. Carpenter, the grandfather of Data Guard. Here a couple of nice new features of (Active) Data Guard in 12gR2:

• Multi-Instance Redo Apply in RAC: Up until now the managed recovery processes (MRP) could only run on a single node on the standby RAC site and hence limited redo apply to the CPU and IO power of that one node. In the new release a coordinator process can distribute the redo data to MPR-processes on all nodes of the RAC cluster. This is called Multi-Instance Apply and is configured as follows:
  Without broker: recover managed standby database disconnect using instances 4;
  With broker: Through the ‘ApplyInstances’ property.
  Caveats in the first 12gR2 release:
  Using Multi-Instance Redo Apply disallows the use of the new feature In-Memory Column Store on Active Data Guard.
  RMAN block change tracking file is disabled.

 

• Data Guard Broker enhancement for Multitenant: As Redo is generated at Container (CDB) level, switchover and failover will also happen for the whole CDB. In 12gR2 there is a new command when using the Data Guard Broker to migrate or failover a Pluggable DB (PDB) to another CDB on the same server:
  
MIGRATE PLUGGABLE DATABASE PDBx TO CONTAINER CDB2 USING PDBx.xml CONNECT AS sys/mypassword@CDB2;

  Depending on what role the CDB I’m connected to has determines if a PDB is migrated to another CDB or is failed over to another CDB. So if e.g. a PDB has a failure on the primary site then I can “failover” its standby-equivalent to another Primary CDB on the standby machine and hence make the “standby PDB” a “primary PDB”. This works best when having 2 CDBs in 2 sites and replicate in opposite directions: CDB1 at site A replicates to CDB1 at site B. CDB2 at site B replicates to CDB2 at site A. So let’s assume PDBx in Primary DB CDB1 fails at site A. You can then migrate PDBx at site B to Primary DB CDB2. PDBx at site A in CDB1 will be dropped automatically, but the CDB2 at site A needs to be manually updated with the new data files of PDBx.

 

• Use In-Memory Column Store on an Active Data Guard DB: As mentioned in my previous BLOG, in 12cR2 In-Memory can be used on an Active Data Guard Instance.
  Restrictions for In-Memory on Active Data Guard:
  In-Memory expressions are captured based on queries executed on the primary only. I.e. the expression statistics store (ESS) is maintained on the primary only.
  Automatic Data Optimization (ADO) policies are triggered only on access recorded on the primary database.
  In-Memory Fast-Start and In-Memory Join-Groups are not supported in an Active Data Guard

 

• Diagnostics and Tuning for Active Data Guard: The Diagnostics Pack (AWR), the Tuning Pack features and SQL Plan Analyzer are supported in the new release on Active Data Guard.
  AWR: In an AWR catalog database the Active Data Guard DB is registered. From there remote snapshots can be taken from the Active Data Guard instance and stored in the AWR catalog: dbms_workload_repository.create_remote_snapshot("TYPICAL", ADG-id);
  SQL Tuning Advisor: All SQL Tuning Advisor Tasks are executed on the Active Data Guard instance. Necessary write activity are done through a DB-Link on the primary DB.

 

• Repair blocks from NOLOGGING-operations: Blocks from NOLOGGING operations on primary can now be validated and repaired on Standby with rman commands:
  
validate/recover ... nonlogged blocks;

  I.e. the primary DB does not necessarily need to be in FORCE LOGGING mode anymore. If NOLOGGING operations are necessary then they can be repaired on the Standby-DB. Previously complete datafiles had to be restored to repair NOLOGGING operations.

On Thursday I visited the panel discussion with the subject “Thinking clearly about Database Application Architecture”. Toon Koppelaars, Connor Mcdonald, Cary Milsap and Gerald Venzl discussed about the correct Application architecture when accessing data in an Oracle Database. The discussion was moderated by Bryn Llewellyn. Toon Koppelaars from the Real World Performance team at Oracle explained why the ThickDB approach by writing business logic (which need data processing) in PLSQL through set or bulk processing is the best method to have a well performing application (see also here). However, today the approach to process the data in layers outside the DB is being preferred (“data to processing” instead of “processing to data”). Unfortunately that results in row by row processing with lots of network roundtrips and higher CPU-usage on the DB-server due to the many times the whole stack on the DB-server has to be traversed.
It was clear and agreed in the audience that the ThickDB approach (“processing to data”) is correct, but why do developers not change their behavior since many years? The opinions on that differed, but also critical statements were expressed that “we as DBAs and DB-Consultants are part of the problem”, because there is no effort to change something in the base education of students to better understand the inner workings of a relational database system and the importance of “processing at the data”.

I’ll leave it to the reader to think about that and end my BLOGs about the Oracle Openworld 2016.

 

Cet article Oracle Open World 2016 – Day 4 and 5 est apparu en premier sur Blog dbi services.

Voici quelques infos sur ce qui a été annoncé ou présenté à l’Oracle Open World. L’info est relayée un peu partout principalement en anglais, donc voici un résumé à l’attention des francophones

Oracle Database 12c Release 2

Soyons clair, la base de donnée n’est pas le sujet principal de l’Open World. Comme prévu, c’est une sortie ‘Cloud First’ mais la version rendu publique lundi est une version limitée.
Si vous avez utilisé le ‘Schema as a Service’ c’est un peu la même idée sauf qu’il s’agit de ‘PDB as a Service’ ici. En multitenant, la consolidation par Schema est remplacée par la consolidation par PDB qui a l’avantage de présenter virtuellement une base complète, avec ses objects publics, ses multiples schemas, etc.
Donc pas d’accès d’administration: c’est un service “managed” – administré par Oracle.
Le multitenant permet de donner des droits DBA sur une PDB tout en empêchant d’interagir avec le reste du système. Ce sont des nouvelles fonctionnalités de la 12.2, entre autres les “lockdown profiles” qui ont été développées dans ce but.
Le service s’appelle “Exadata Express Cloud Service” car il tourne sur Exadata (donc compression HCC et bientôt SmartScan). La plupart des options sont d’ailleurs disponibles (In-Memory, Advanced Compression,…)
“Express” est pour la facilité et rapidité de provisonning: quelques minutes. Le but est qu’un développeur puisse en 5 minutes créer un service base de donnée facilement accessible (par SQL*Net encrypté). L’idée c’est qu’il soit aussi facile pour un développeur de créer une base Oracle que de créer des bases Postgres, Cassandra, MongoDB,…
Et bien sûr si on met toutes les option, le développeur va les utiliser et elles deviendront nécessaires en production.

Il y aura bientôt un Data Center en Europe. Pour le moment, c’est seulement aux USA. Le prix est attractif (CHF 170 par mois) mais la base est assez limitée en terme de CPU, stockage et mémoire. C’est principalement pour du développement et du bac à sable.

Donc la 12c Release 2 pour le moment n’est disponible que sous la forme de PDBaaS sur Exadata Express Cloud Service:

Avant la fin de l’année, on devrait avoir la 12.2 en DBaaS (non-managed que l’on connait actuellement sir le PaaS Oracle) et la version General Availability viendra ensuite, probablement en 2017

 

Cet article OOW 2016: nouveautés base de donnée est apparu en premier sur Blog dbi services.

Last week (09/12/2016) was announced the new MySQL 8.0.0 DMR (Development Milestone Release)
It is now available for download at dev.mysql.com
I downloaded and installed it
Following are my first impression on some new features
First of all, when you remember the size of earlier versions, it is more & more gluttonous, see below
mysql-5.0.96-linux-x86_64-glibc23.tar.gz    121.2M
mysql-5.1.72-linux-x86_64-glibc23.tar.gz    127.8M
mysql-5.5.52-linux2.6-x86_64.tar.gz            177.2M
mysql-5.6.33-linux-glibc2.5-x86_64.tar.gz    299.7M
mysql-5.7.15-linux-glibc2.5-x86_64.tar.gz   611.8M
mysql-8.0.0-dmr-linux-glibc2.12-x86_64.tar.gz is around 1Gb and uncompressed 3.6Gb (Oups…)

At first sight , it seems that nothing has changed, same schemas and almost the same tables
– 2 new tables related to roles in the mysql schema : default_roles, role_edges
– 6 new tables in the information_schema & 6 also in the performance_schema

When you scan your Data directory (datadir), you will find new “.SDI” files (Serialized Dictionary Information) for every schema except for MySQL
mysql@MYSQL:/u01/mysqldata/mysqld9/ [mysqld9] ll *.SDI
-rw-r-----. 1 mysql mysql 215 Sep 13 21:34 employees_4.SDI
-rw-r-----. 1 mysql mysql 225 Sep 13 21:37 performance_sche_7.SDI
-rw-r-----. 1 mysql mysql 209 Sep 13 21:34 sys_6.SDI
-rw-r-----. 1 mysql mysql 209 Sep 13 21:34 TBS_3.SDI
If you have a look in one of these files, you will see that they all provide data dictionary information in a serialized form (JSON formatted text)
mysql@MYSQL:/u01/mysqldata/mysqld9/ [mysqld9] cat employees_4.SDI
{
"sdi_version": 1,
"dd_version": 1,
"dd_object_type": "Schema",
"dd_object": {
"name": "employees",
"default_collation_id": 8,
"created": 0,
"last_altered": 0
}
Old “.frm” files containing metadata  have been removed, the same for “.par” file (Partition definition), “.trg file” (Trigger parameter) and “.isl” file (InnoDB Symbolic Link)
When you create a new INNODB table, metadata are stored now in the InnoDB file (.ibd)
For all the other storage engine (memory, CSV,Blackhole, etc…), we get now a new “.SDI” file but more complex
mysql@MYSQL:/u01/mysqldata/mysqld9/Newfeatures/ [mysqld9] cat t3_617.SDI
{
"sdi_version": 1,
"dd_version": 1,
"dd_object_type": "Table",
"dd_object": {
"name": "t3",
"mysql_version_id": 80000,
"created": 20160914075838,
"last_altered": 20160914075838,
"options": "avg_row_length=0;key_block_size=0;keys_disabled=0;pack_record=0;stats_ auto_recalc=0;stats_sample_pages=0;",
"columns": [
{
"name": "c1",
"type": 29,
"is_nullable": true,
"is_zerofill": false,
"is_unsigned": false,
"is_auto_increment": false,
"is_virtual": false,
"hidden": false,
"ordinal_position": 1,
"char_length": 20,
"numeric_precision": 0,
"numeric_scale": 0,
"datetime_precision": 0,
"has_no_default": false,
"default_value_null": true,
"default_value": "",
"default_option": "",
"update_option": "",
"comment": "",
"generation_expression": "",
"generation_expression_utf8": "",
"options": "interval_count=0;",
"se_private_data": "",
"column_key": 1,
"column_type_utf8": "char(20)",
"elements": [],
"collation_id": 8
}
],
"schema_ref": "Newfeatures",
"hidden": false,
"se_private_id": 18446744073709551615,
"engine": "MEMORY",
"comment": "",
"se_private_data": "",
"row_format": 1,
"partition_type": 0,
"partition_expression": "",
"default_partitioning": 0,
"subpartition_type": 0,
"subpartition_expression": "",
"default_subpartitioning": 0,
"indexes": [],
"foreign_keys": [],
"partitions": [],
"collation_id": 8
}
It is possible now to create roles, something we were waiting for years, that means you can define a set of privileges as a role and assign it to a user
mysqld9-(root@localhost) [Newfeatures]>create role tstrole;
mysqld9-(root@localhost) [Newfeatures]>grant all on employees.* to tstrole;
mysqld9-(root@localhost) [Newfeatures]>select host, user from mysql.user;
+---------------+-------------+
| host | user |
+---------------+-------------+
| % | tstrole |
As you can see, roles are stored in the mysql.user table meaning that you can assign a user to another user
mysqld9-(root@localhost) [Newfeatures]>show grants for tstrole;
+----------------------------------------------------------+
| Grants for tstrole@% |
+----------------------------------------------------------+
| GRANT USAGE ON *.* TO `tstrole`@`%` |
| GRANT ALL PRIVILEGES ON `employees`.* TO `tstrole`@`%` |
+----------------------------------------------------------+
mysqld9-(root@localhost) [Newfeatures]>grant tstrole to 'sme'@'localhost';
mysqld9-(root@localhost) [Newfeatures]>show grants for 'sme'@'localhost' using tstrole;
+----------------------------------------------------------------------------------+
| Grants for sme@localhost |
+----------------------------------------------------------------------------------+
| GRANT USAGE ON *.* TO `sme`@`localhost` |
| GRANT ALL PRIVILEGES ON `employees`.* TO `sme`@`localhost` |
| GRANT `tstrole`@`%` TO `sme`@`localhost` |
+----------------------------------------------------------------------------------+
Now we connect as user “sme”
mysql -usme -p
mysql> use mysql
ERROR 1044 (42000): Access denied for user 'sme'@'localhost' to database 'mysql'
It seems to work, as user “sme” has only access to the employees schema

Data dictionary has been improved, almost all the system tables have been moved from MyISAM to the transactional InnoDB storage engine to increase reliability
Data dictionary tables are invisible,  they do not appear in the output of SHOW TABLES and cannot be accessed directly
but in most cases there are corresponding INFORMATION_SCHEMA tables that can be queried instead.

The new feature “Invisible Indexes” is really great.
You can toggle  now the visibility of an index as VISIBLE or INVISIBLE
We know that because of unused indexes, performance of modifications (insert, updates) are reduced
As they are also for the optimizer because they are taken in account for the plan selection
So first check for unused indexes
mysqld9-(root@localhost) [information_schema]>SELECT * FROM sys.schema_unused_indexes;
+------------------+-------------------+---------------+
| object_schema | object_name | index_name |
+------------------+---- --------------+---------------+
| employees | departments | dept_name |
| employees | dept_manager | dept_no |
+------------------+-------------------+---------------+
then
mysqld9-(root@localhost) [employees]>alter table departments alter index dept_name INVISIBLE;

Check in the data dictionary
mysqld9-(root@localhost) [employees]>SELECT * FROM information_schema.statistics WHERE is_visible='NO'\G
*************************** 1. row ***************************
TABLE_CATALOG: def
TABLE_SCHEMA: employees
TABLE_NAME: departments
NON_UNIQUE: 0
INDEX_SCHEMA: employees
INDEX_NAME: dept_name
SEQ_IN_INDEX: 1
COLUMN_NAME: dept_name
COLLATION: A
CARDINALITY: NULL
SUB_PART: NULL
PACKED: NULL
NULLABLE:
INDEX_TYPE: BTREE
COMMENT:
INDEX_COMMENT:
IS_VISIBLE: NO
You can make now persistant global variables
select @@max_connections;
+--------------------------+
| @@max_connections |
+--------------------------+
| 151 |
+--------------------------+
SET GLOBAL max_connections=200;
If you restart your Instance, such setting is lost. So now with
SET PERSIST max_connections=200;
This setting now will remain after an instance restart
select @@max_connections;
+--------------------------+
| @@max_connections |
+--------------------------+
| 200 |
+--------------------------+
Last but not least, be carefull when using MySQL 8.0.0.0 in a multi instance environment,
in my case 9 instances with different versions
I found a bug in mysqld_multi when you want to restart your instance 8.0.0.0
First I corrected the still not fixed Bug #77946 (https://bugs.mysql.com/bug.php?id=77946)
in order to be able to stop my instance properly with mysqld_multi
I stopped it and then tried several times to restart it
No way
2016-09-20T23:42:41.466540Z 1 [ERROR] InnoDB: Operating system error number 2 in a file operation.
2016-09-20T23:42:41.466562Z 1 [ERROR] InnoDB: The error means the system cannot find the path specified.
2016-09-20T23:42:41.466568Z 1 [ERROR] InnoDB: If you are installing InnoDB, remember that you must create directories yourself, InnoDB does not create them.
2016-09-20T23:42:41.466574Z 1 [ERROR] InnoDB: File ./ibdata1: 'open' returned OS error 71. Cannot continue operation
2016-09-20T23:42:41.466582Z 1 [ERROR] InnoDB: Cannot continue operation.

As a temporary workaround, you can either start it manually or use the mysqld_multi from a previous version
I reported this bug  to MySQL (https://bugs.mysql.com/83081)

 

Cet article MySQL 8.0.0 DMR – First impression est apparu en premier sur Blog dbi services.

On day 3 I visited various sessions about In-Memory and its many new features in 12gR2. Yesterday I already listed some new features of In-Memory. In this post I want to explain the new features more in detail:

 

In-Memory Join Groups:

Columns are specified, which are used to join tables:

CREATE INMEMORY JOIN GROUP V_name_jg (VEHICLES(NAME), SALES(NAME));


Those columns share the compression dictionary. My understanding on how this works is as follows: The joins occur on dictionary values rather than data. E.g. a dictionary with distinct values of car brands (column NAME in VEHICLES and SALES) may look as follows:

BMW 1
VW 2
Mercedes 3
Ford 4
Fiat 5
Dodge 6

The dictionary values are stored in the compression units instead of the real data:

1
1
2
3
3
3
4
5
5
6

Doing that for the 2 columns allows the joins to happen on the dictionary values rather than real values. Oracle talks about a speedup of a factor 2-3 when using Join Groups.

 

In-Memory expressions:

SQL expression results (NET in the example below) can now be stored as additional in-memory columns:

CREATE TABLE SALES (
PRICE NUMBER, TAX NUMBER, ...
NET AS (PRICE + PRICE * TAX )
)
INMEMORY;


All in-memory optimizations (e.g. vector processing or storage indexes) apply to the expression columns as well. When a SQL contains the expression then it can be taken from the column store without computing it:

SELCT SUM(NET) FROM SALES WHERE NET > 50;


Different types of expressions are possible:

• Arithmetic expression
• Logical expression (e.g. DECODE)
• Type conversion (e.g. UPPER, TO_CHAR)
• PL/SQL expressions

Two modes to define the expressions to populate (Manual and Auto) can be used:

Manual: Declare virtual columns for the desired expression (see example above). The parameter INMEMORY_VIRTUAL_COLUMNS defines if virtual columns are considered for inmemory:
INMEMORY_VIRTUAL_COLUMNS
= ENABLE: All user-defined virtual columns on the table or partition enabled for in-memory will be populated
= MANUAL: User-defined virtual columns must explicitly marked for INMEMORY (default)
= DISABLE: No user-defined column will ever be populated

Auto: Oracle detects frequent expressions automatically. I.e. the optimizer stores “hot” expressions (based on frequency and cost) in the expression statistics store (ESS). With the procedures IME_CAPTURE and IME_POPULATE in the package DBMS_INMEMORY the expressions are captured and declared as hidden in-memory virtual columns on the appropriate table. Expressions in the ESS can be checked by querying ALL|DBA|USER_EXPRESSION_STATISTICS.

 

In-Memory JSON

JSON columns and expressions on JSON columns can now be populated in-memory.

 

In-Memory on Active Data Guard

According Oracle, In-Memory on Active Data Guard was the most wanted feature from customers for In-Memory for 12gR2. I.e. the In-Memory column store can now be used on the Active Data Guard instance as well. The standby database can have different data (columns) stored in-memory than the primary. The decision on what columns to populate in-memory on the different instances is based on a service. I.e. on primary the following DDL may be used:

ALTER TABLE SALES INMEMORY DISTRIBUTE FOR SERVICE A;
ALTER TABLE SHIPMENTS INMEMORY DISTRIBUTE FOR SERVICE B;


Table SALES will be populated In-Memory on that instance, which has service A enabled and SHIPMENTS will be populated on the instance, which has service B enabled.

 

In-Memory Columnar Flash

On Exadata the In-Memory format can be used on the Flash Cache. I.e. an In-Flash Column store can be created. The advantage is that there is usually much more Flash than RAM and hence more data can be cached for In-Memory on Flash scans. To do that the CELLMEMORY segment attribute is available:

ALTER TABLE sales CELLMEMORY;
CREATE TABLE trades (...) CELLMEMORY MEMCOMPRESS FOR QUERY;


Restrictions in comparison to normal In-Memory:

• The MEMCOMPRESS sub-clause only supports “FOR QUERY LOW” and “FOR CAPACITY LOW”.
• There is no PRIORITY sub-clause.

 

Automatic Data Optimization (ADO) extended to In-Memory

The heatmap can now be used to define how long data should remain In-Memory or when In-Memory compression should be changed. I.e. in the maintenance window or on manual request (using the procedure DBMS_ILM.EXECUTE_ILM) Oracle checks if a policy has been met to e.g. flush data from the In-Memory column store.

ALTER TABLE sales ILM ADD POLICY ... NO INMEMORY AFTER 10 DAYS OF NO ACCESS;


That allows sliding windows of column store content based on access-time or time of creation. A customized policy function can also be created in PLSQL.

 

In-Memory Fast-Start

The In-Memory column store content can now be checkpointed to Securefile Lobs. When the DB restarts the population is faster (between 2-5x) as the data can immediately be loaded in memory without CPU-intensive compression activity. To activate In-Memory Fast-Start the procedure DBMS_INMEMORY_ADMIN.FASTSTART_ENABLE with a tablespace-name as parameter has to be executed. The tablespace should be 2 times the size of the in-memory column store.

 

Cet article Oracle Open World 2016 – Day 3 est apparu en premier sur Blog dbi services.

I’m at Oracle Open World and I’m rather focused on database rather than all those Cloud topics, but one product caught my attention at the Oracle ACED Briefing. Oracle bought Ravallo systems at the beginning of the year. What is Ravello? You have virtualized your applications on VMware and want to move them to the Cloud… without any changes.

Move your application

An application is not a single VM. It’s an ecosystem of VMs working together, linked by one or multiple network interfaces. Moving the virtual machines is easy, thanks to virtualization. But do you change the IP addresses everywhere? This is where you need another layer of virtualization.

Let’s see how it works. With Ravallo you can import your VMs easily. It can connect to your VSphere or you just import an ova. Once they are imported into Ravallo, you can start to build your application with a simple drag and drop of the concerned VMs.

The magic follows. Ravallo parses the VMs metadata and data to discover the ecosystem. Here his the result after having importing a database, two weblogic server servers, and a windows client:

Not only the VMs are there. there is a network here with switches, routers, DNS, DHCP, a fenced network private to my application, all virtualized.

And there’s more: all IP addresses are the same in that private network than on my on-premises VMWare farm. That’s the point. Changing network interfaces, IP addresses, DNS, etc is a nightmare and you don’t have to do it.

This is only the design of the application. Once that application is defined, you can publish it to the Cloud: Oracle Public Cloud, Google one, or AWS.

And this is easy. You can choose that resources are optimized for cost or performance, and you even have an idea of the price:

Time to run our application. As it runs in an isolate environment, you can even run multiple instances of it. But how do you connect to it?

First, you can access the console to each VM from Ravallo though VNC.
For external access you create services that set NAT rules and allocate public IP addresses.

Ravallo is nested virtualization: two levels of hypervisors.

 

Cet article Ravello est apparu en premier sur Blog dbi services.

When 12.1 came out, the major issue we encountered after migration was related to the new adaptive features of the optimizer: automatic reoptimization, SQL Plan Directives and the resulting dynamic sampling. Of course, Oracle product managers listen to feedbacks, ensure to provide workarounds or fixes and make things better for next release. Let’s see what has been announce on this topic for 12.2

Fixing vs. workarounds

Unfortunately, in most case, when a problem is encountered people put priority on it only until the issue appears as “solved”, and then close the problem. However for stability and reliability, this is not enough. There are two phases in problem resolution:

1. Make broken things working again as soon as possible
2. Ensure that the solution addresses the root cause and is in the same scope as the problem

If you stop after the first point, you don’t have a solution. You have a workaround, and two things will happen soon or later:

• The problem will come back again
• New problems will appear as side effects

12.1

So, when you upgrade to 12c from 11.2.0.4 for example, the easiest way to fix a regression is to set optimizer_features_enable=’11.2.0.4′. But when you do that, you did only the first step. Nothing is fixed. Actually, when doing that you didn’t even finish your upgrade job.
I’ve already blogged about how to fix an adaptive statistics issue and keep the fix in the same scope as the problem by:

• Disabling the SQL Plan Directives that cause problem
• Disabling the feature that cause problem

so there are many combinations that depend on your context.

One parameter do not fit all

It’s easy to disable all new adaptive features and claim that the 12c optimizer is full of bugs. However there are two things that I’m sure:

• The developers of the optimizer know their stuff at least 100x better than I do
• They want to bring nice features rather than trying to break things

And they do something very nice: each individual feature can be enabled or disabled by a parameter. So there are lot of parameters. Some of them are undocumented just because at release time they don’t think they should have a different value other than default, except special situations guided by the support. But one set of default value cannot fit all environments. Are you doing OLTP or BI? OLTP likes stability, BI likes adaptive optimization. And probably your database has both OLTP and reporting workloads, and maybe at the same time. This is the first reason why one set of parameter cannot fit all. There’s another one you should think about before blaming the optimizer. Maybe they bring features that helps to make good applications even better. Maybe the set of default value is not chosen to fit the worst application design…
Let’s come back to the OLTP vs. BI example. Adaptive features are enabled by default for BI. You may spend more time on parsing in order to get the optimal execution plan. But then you complain that your OLTP spends more time on parsing… But you are not supposed to parse on OLTP! The overhead of adaptive features should not be a blocking problem if you parse your queries once and then execute them.

I tend to blog on encountered issues rather that on thinks that do not raise any problem. Because my job is to solve problems rather that stay looking at what works well. I’ve encountered a lot of issues with those adaptive features. But I have seen lot of application that had no problem at all when upgraded to 12c. When you disable the adaptive features, do you workaround an optimizer problem, or your application design problem?

12.2

In 12.1 only optimizer_adaptive_features is documented but it disables too many features. You may want to disable SQL Plan Directive and their consequences. But you probably want to keep adaptive plans as they are awesome and less prone of bad side effects. So in 12.2 this parameter has been split into two parameters: OPTIMIZER_ADAPTIVE_PLANS and OPTIMIZER_ADAPTIVE_STATISTICS

In addition to that, only OPTIMIZER_ADAPTIVE_PLANS is set to true by default. OPTIMIZER_ADAPTIVE_STATISTICS is false so by default you will not have the following 12c features: SQL Plan Directives, Statistics feedback, Performance feedback, Adaptive dynamic sampling for parallel query.

Here are the features enabled by OPTIMIZER_ADAPTIVE_PLANS:

optimizer_adaptive_plans TRUE FALSE _optimizer_nlj_hj_adaptive_join TRUE FALSE _px_adaptive_dist_method CHOOSE OFF _optimizer_strans_adaptive_pruning TRUE FALSE

If you want more information about them, I’ve written articles about adaptive join, adaptive PX distribution and adaptive star transformation bitmap pruning

Here are the features enabled by OPTIMIZER_ADAPTIVE_STATISTICS:

optimizer_adaptive_statistics FALSE TRUE _optimizer_dsdir_usage_control 0 126 _optimizer_use_feedback_for_join FALSE TRUE _optimizer_ads_for_pq FALSE TRUE

As you can see there is no “_optimizer_gather_feedback” here so the cardinality feedback coming from 11g is still there when you disable adaptive statistics. You may like it or not, and maybe want to disable cardinality feedback as well if you don’t want plans that change.

What if you already have some SPDs? as “_optimizer_dsdir_usage_control” is 0 they will not be used. And they will be dropped automatically after 53 weeks of no usage.

 

Cet article Oracle 12cR2 Optimizer Adaptive Statistics est apparu en premier sur Blog dbi services.

Wie auch in den letzten Jahren werden wir auch dieses Jahr wieder einen Schlungstag an der DOAG ausrichten. Dieses mal wird sich alles um die Oracle Clusterware (“Infrastruktur & Middelware” –> “Oracle Grid Infrastructure”) drehen: Los geht es mit den Anforderungen an Netzwerk, Speichersysteme, Betriebssystem und Kernel Parameter, denn nur wenn die Basis auch stimmt arbeitet eine Cluster-Lösung auch verlässlich. Wie immer bei uns wird es zahlreiche Live Demos geben, denn zeigen ist immer besser als nur erzählen. Es geht dann weiter mit der Architektur, der Installation, Konfiguration und dem Betrieb der Lösung. Natürlich gehen wir auch detailliert auf die Fehlersuche und Analyse ein. Am Ende des Tages sollte jedem klar sein was genau die Oracle Clusterware ist, wofür man sie einsetzen kann und sollte und auf was genau zu achten ist. Oracle selbst setzt die Clusterware bei fast allen Engineered Systems sowieso schon ein, also lieber gleich wissen worauf es ankommt.
Wer dann immer noch das Gefühl hat mehr Praxis zu benötigen kann sich gerne unseren Workshop zum selben Thema ansehen.

Wir freuen uns jetzt schon auf die zahlreichen Besucher an der DOAG 2016.

 

Cet article DOAG 2016, Schulungstag: Oracle Grid Infrastructure est apparu en premier sur Blog dbi services.

Day 2 is the first official day of the Oracle Open World (OOW) 2016. As a parallel event the Oak Table Network organized his Oak Table World (OTW) close to the Open World. I attended several sessions from OOW and OTW:

Jeremy Schneider: Ansible

Ansible is a very light software written in Python, which allows automation in deploying applications and managing systems. The main goal of the developer of Ansible Michael DeHaan was to make the process of deploying software and managing systems much simpler than it is with Puppet or Chef. Jeremy Schneider showed a demo on how easy it is to manage many systems with such an easy and still very effective tool, which uses ssh to connect to the servers and execute commands. It was impressive to see and I feel I have to check with my customer running on Redhat, if Ansible could not be an alternative to Puppet.

Frits Hoogland: Drilldown into logwriter mechanics

What happens when a user executes a “COMMIT;” ? Yes, we know that the logwriter is triggered to write the data to disk. But what happens in detail? By using the debugger dbg on Linux and setting break points in various modules, Frits could show in a very technical session what exactly happens when the foreground process runs in polling mode (i.e. instead of having the Log-Writer triggering the foreground process that the data is persistent on disk, the foreground process is polling SCN-information to detect that the data is on disk). See here.

Wei Hu, John Kanagaraj: High Availability and Sharding Deep Dive with Next-Generation Oracle Database

What is Sharding? According Oracle there is a need for World Scale applications to have a farm of independent databases. I.e. instead of 1 giant DB, the DB is partitioned into many smaller DBs (shards) running on different hosts. In contrast to RAC the data is not shared, i.e. every machine has its own disks (shared nothing hardware). So each shard stores a subset of the data. For performance reasons read-mostly data (e.g. a lookup table) is replicated between the shards. The applications have to be designed in a way that workload can be routed to a specific database in the farm. There is a choice of the sharding method: System managed (consistent hash), Composite (range-hash, list-hash) and User defined (range, list). Based on a sharding key (in the example below the CustId) the data is distributed among the shards:


CREATE SHARDED TABLE
...
PARTITION BY CONSISTENT HASH (CustId)
...;


In case a new shard is added, the data needs to be redistributed. That move of data is initiated automatically or manually (by the DBA). When it’s automated the system uses RMAN Incremental Backups and Transportable Tablespaces to redistribute the data.

Enhancements with Active Data Guard:

Improved Data Protection:

• High speed DB compare (whole DB or individual data files) between Primary and Standby. Validates that primary and standby is physically the same, by doing a compare at the physical level.
• RMAN validation and repair of blocks on standby that were invalidated by non-logged operations (e.g. direct path loads) on the primary.
• Improved automatic block repair.

Active Data Guard enhancements:

• During switchover/failover the read-only sessions remain connected and become read/write after the Active Data Guard becomes
• Primary. That avoids a reconnect strorm after the switchover/failover.
• In-memory DB now possible on Active Data Guard. The columns defined for In-Memory can be different on Primary and STandby.
• Support of Diagnostic Pack (AWR), Tuning Pack and SQL Plan Analyzer on the Standby System.
• Passwd file on standby is automatically updated.
• Standby-first encryption: Can encrypt tablespaces on standby first, switchover and then encrypt on old primary, so that encryption can be enabled without much downtime.

 

Nigel Bayliss: Upgrading to Oracle 12c without Pain.

Nigel talked about new 12.2 Optimizer features. In 12cR1 the Optimizer adaptive features (adaptive plans and adaptive statistics with SQL Plan directives) were controlled by 1 parameter: OPTIMIZER_ADAPTIVE_FEATURES. In 12cR2 the adaptive plans and adaptive statistics have their own parameters: OPTIMIZER_ADAPTIVE_PLANS (default TRUE) and OPTIMIZER_ADAPTIVE STATISTICS (default FALSE). I.e. in 12cR2 adaptive plans are enabled by default. SQL Plan Directives will still be created, but are not used by default. So the new default settings are closer to the 11g behavior as SQL Plan Directives are not used.
For migrations to 12cR2 Nigel provided specific cook books to follow to avoid plan changes initially (use SQL Plan Baselines to fix e.g. 11g plans) and then evolve to 12c.

Juan Loaiza: Oracle Database In-Memory: What’s New and What’s Coming

New features are:

• Faster In-Memory joins: Join Groups can be defined. They specify columns, which are frequently used to join tables. The columns share the compression dictionary. The join occurrs on dictionary values rather than data: CREATE INMEMORY JOIN GROUP V_name_jg (VEHICLES(NAME), SALES(NAME)); That should bring up to 2.3 times faster join processing.
• Precomputed expressions (e.g. Price + Price * Tax) can be cached In-Memory as user defined virtual columns. I.e. using such an expression in the query can gain from In-Memory data access.
• In-Memory on Active Data Guard (see above).
• In-Memory columnar format can be used on Exadata Flash Cache.
• Data lifecycle management of In-memory data. I.e. policeis can be defined to evict cold data from the In_memory Column Store.
• On engineered systems the IM column data can be persisted on storage. After a restart the data can be loaded faster in memory.

 

Cet article Oracle Open World 2016 – Day 2 est apparu en premier sur Blog dbi services.

This morning during Gerald Venzl presentation of “What’s New for Developers in the Next Generation of Oracle Database” at Oracle Open World, one feature has been acclaimed by a full room: 12.2 show the end of identifiers limited to 30 characters.

12.1

We knew it would happen because in 12.1 all data dictionary views have 128 bytes length character strings:

Connected to:
Oracle Database 12c Enterprise Edition Release 12.2.0.1.0 - 64bit Production
 
SQL> desc dba_objects
Name Null? Type
----------------------------------------- -------- ----------------------------
OWNER VARCHAR2(128)
OBJECT_NAME VARCHAR2(128)
SUBOBJECT_NAME VARCHAR2(128)

but that’s only the dictionary metadata. Impossible to reach that limit:

SQL> create table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" as select * from dual;
create table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" as select * from dual
*
ERROR at line 1:
ORA-00972: identifier is too long

It is only annoying as the default column format do not fit in the screen:

SQL> select owner,object_name from dba_objects where object_type='TABLE';
 
OWNER
------------------------------------------------------------------------------------------------------------------------
OBJECT_NAME
------------------------------------------------------------------------------------------------------------------------


12.2

In 12.2 you can create longer identifiers:

SQL> create table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" as select * from dual;
Table created.
SQL> alter table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" add XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX number;
Table altered.

But be careful, the limit is in bytes – not in characters. If we have multibytes characters, the limit can be reached earlier:

SQL> alter table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" add X€XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX number;
alter table "ThisIsAVeryLongNameThatIsAllowedInTwelveTwoC" add X€XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX number
  *
ERROR at line 1:
ORA-00972: identifier is too long


So what?

The goal is not to abuse and put the longest names possible. But allowing more that 30 characters can be easier to match table names with Java class names for example.

Oracle 7

I wanted to show that those 30 characters limits was very old, so I ran a 7.3.3 oracle version that lies on my laptop and displayed the same describe of DBA_OBJECTS:

Identifiers were 30 characters there. But look at object name: those 128 bytes are there for more than 20 years!

 

Cet article Oracle 12cR2 Long Identifiers est apparu en premier sur Blog dbi services.

Oracle Open World 2016 started on Sunday. The first day is always reserved for presentations provided by members of the various Oracle User Groups. However, the last part of the day is the first Keynote from Larry Elison. But let’s start by some of the sessions I visited Sunday:

Ludovica Caldara: Migrating to Oracle Databases 12c: 300 databases in 300 days.

Ludovica provided a presentation about the experience he gained during the migration project of 300 databases to 12c: Issues they faced and things to consider when migrating to 12c.
The main recommendations to avoid performance issues after the migration to 12c were related to SQL Plan Directives. I do not want to go into too much detail on the topic, but one issue Ludovica’s customer faced in terms of SQL Plan Directives was related to high CPU utilization at specific, fixed times when a system-job called the function DBMS_FEATURE_AWR. For details on this subject see here.
Other things to consider are the Oracle recommended patches from MOS-Note 2034610.1 (Things to Consider to Avoid Poor Performance or Wrong Results on 12.1.0.2).

Franck Pachot: Single-Tenant Oracle Database 12c: Multitenant Features for All Editions

In his excellent session Franck presented about some good reasons to go to Single-Tenant databases instead of running the deprecated Non-Container databases (i.e. the only way DBs could be run up to 11gR2 with 1 DB per Instance). Among other things the possibility to transport a database to another machine by un-plug and plug-in and 12.2.-security features were mentioned (use of the new lockdown profile, which can e.g. disable database options for a pluggable database).

Mauro Pagano: SQLd360: SQL Tuning Diagnostics Made Easy

Being very excited about the free software SQLd360 Mauro developed (see here), he enthusiastically presented the history of tuning single SQL-statements during the various phases of available tools and database features:

• 1998, when not much data was available about the history of a SQL-statement
• 2007, when SQLTXPLAIN became very popular
• today with the availability of SQL_MONITOR and Active Session History

Bottomline is that SQLd360 should be the tool to use today to tune a single SQL-statement, because of various advantages compared to SQLT(XPLAIN) (took the following list from here):

• not necessary to install something on the database
• SQLd360 is 100% free software, while SQLT requires a My Oracle Support (MOS) account, and some consultants and third parties may struggle to obtain a valid login for MOS or would have to use their client’s credentials.
• SQLd360 makes use of newer technologies including Google Charts, presenting the metadata in a very “Wow!” way, while SQLT focuses on HTML tables.
• SQLd360 is 13X smaller in terms of lines of code, and it pretty much does the same job as SQLT
• SQLd360 is much faster to execute than SQLT.

Sunday Keynote by Larry Ellison:

Remark: I do not talk about the Cloud here (almost all of the Keynote was news about Oracle’s Cloud), as I want to concentrate on what’s coming on the DB-side.

First info on Oracle DB 12c Release 2:

• Multitenant
  Agility with on-line clones and on-line relocate
  4095 PDBs possible (255 in 12.1)
• Sharding: A shared nothing architecture where databases on different nodes form a logical database.
  It provides elastic scalability with native sharding for global-scale applications.
• In-Memory
  Column-Store on Active Dataguard
  Increased performance (up to 60x faster than 12.1)

 

Cet article Oracle Open World 2016 – Day 1 est apparu en premier sur Blog dbi services.

It’s official, Larry Ellison made the annoucement at first keynote and the database product team at oracle has released the version and the documentation publicly. Oracle Database Exadata Express Cloud Service is the ‘Cloud First’ environment for 12.2

Documentation

Documentation is there: Cloud > Platform > Data Management > Exadata Express
The 12.2 new features available in that ‘Cloud First’ are documented here

Cloud First

We knew it, 12.2 comes ‘Cloud First’ which means that you cannot download it but you can use it on a Cloud Service. This is in my opinion a very good idea. We will not upgrade all our databases to 12.2 so it’s beter to test it and cloud services are good for that.
However the way it is released is quite limited:

• There is no free trial. You have to pay for the minimum service to test it (175$/month)
• Features are very limited because the service is a PDB, not a full database

PDBaaS

This Oracle Database Exadata Express Cloud Service is a fully managed service, wich means that you are not the database administrator. Oracle manages the system, creates and administrate the database. You are a user.
Actually, when you create a service, a Pluggable Database is provisioned for you and you access only this PDB. It addition to that, for security reason, all features that may interact with the other PDBs or the system, are locked down. For example, you cannot use Data Pump because it writes files on the server. All limitations are documented here.
If you wonder how those limitations are implemented, it’s a new 12.2 multitenant feature called lockdown profiles, and resource manager that can isolate PDB memory. I presented that yesterday at Oracle Open World and there is more information about it in new book to come.

Options

Features are limited but you have most of options available: In-Memory, Data Mining, Advanced Compression and Hybrid Columnar Compression, Data Redaction, etc. And it’s an Exadata behind so you have SmartScan.

You can think of it as the ‘Schema as a Service’, but with a PDB instead of a schema.

You access to it only through SQL*Net (encrypted) and can move data to and from using SQLDeveloper.

Shapes

When you see ‘Exadata’, ‘In-Memory’, and all those options, you probably think about a service for very big database and high CPU resources. But it is not. This service is for evaluation of the 12.2, testing, developement, training on very small databases (few hundred of GB). And only one OCPU (which is an intel core with two threads). It’s hard to imagine more than one user on this. Maximum memory being 5GB it’s also hard to imagine In-Memory here.

So the goal is clearly to test feature, not to run workloads. You can go live with it only if your production is not critical at all (database is backed up daily).

Express

The ‘Express’ part is the simplicity. Prices are easy to calculate:

• 175$/month for 20GB of storage and one OCPU. This is ‘X20′ service.
• Next level is the ‘X50′ service at 750$/month, so x2.5 times the storage for x4.2 the price. Still one OCPU.
• Highest level is ‘X50IM’ at 950$/month, which is the same but with larger memory.

Non-Metered

It is a non-metered service: whether you use it or not you pay per month. But don’t think you can do whatever you want within that month as the transfer of data is limited. You can transfer the volume of the database only a few times per month.

So what?

The utilization is simple: you don’t need a DBA. This is the main point: automation and fast provisioning.
Developers will love that. Giving them full options is a good marketing idea. Once the application is designed to use In-Memory, Compression, etc. theses options will be required for production as well.

Today, developers need more agility and are often slowed down by the operations. And that’s a major reason why they go to other products that they can install and use themselves easily: Postgres, Cassandra, MongoDB, etc. Oracle Database is to fat for that: look at the time you need to create a database, catalog, catproc, etc. A first answer was the Oracle XE edition which is easy to install anywhere. Now with this Express Cloud Service Oracle gives to possibility to provision a small database in minutes which requires no further administration.
Actually, this is the whole idea behind the multitenant architecture: consolidate all those system objects created by catalog/catprocg into a common location (CDB$ROOT) and have light PDBs with only user data.

Final remark. Currently 12.2 is available on on that service but there are no doubts that a full 12.2 will come within the next months.

 

Cet article Oracle Database 12.2 – PDBaaS est apparu en premier sur Blog dbi services.

Last week, dbi services organized an event named “SQL Server 2016: what’s new?” in Lausanne, Basel and Zurich. I would take the opportunity to say again a big thank you to everyone which joined us.
During my session some questions concerning the new functionality Dynamic Data Masking were asked. In fact data are masked for some roles and not for some others.
Let’s try to clarify that.

I will use the same script I used during the event to initialize the database, create the table and fill-in my table with some rows:

-- Create database
USE MASTER
GO
CREATE DATABASE DDM_TEST
GO

-- Create the Confidential table
USE [DDM_TEST]
GO

CREATE TABLE [dbo].[Confidential](
[ID] [int] NULL,
[Name] [nvarchar](70)NULL,
[CreditCard] [varchar](16)NULL,
[Salary] [int] NULL,
[Email] [nvarchar](60)NULL
)ON [PRIMARY]

-- Insert some rows
INSERT INTO [dbo].[Confidential] VALUES ('1','Stephane','3546748598467584',113459,'sts@dbi-services.com')
INSERT INTO [dbo].[Confidential] VALUES ('2','David','3546746598450989',143576,'dab@dbi-services.com')
INSERT INTO [dbo].[Confidential] VALUES ('3','Nathan','3890098321457893',118900,'nac@dbi-services.com')
INSERT INTO [dbo].[Confidential] VALUES ('4','Olivier','3564890234785612',98000,'olt@dbi-services.com')
INSERT INTO [dbo].[Confidential] VALUES ('5','Alain','9897436900989342',85900,'ala@dbi-services.com')
INSERT INTO [dbo].[Confidential] VALUES ('6','Fabrice','9083234689021340',102345,'fad@dbi-services.com')

I will create some masks for confidential columns with the following script:

-- create data masking for confidential columns with masking functions
USE DDM_TEST
GO

ALTER Table Confidential
ALTER COLUMN Salary ADD MASKED WITH (FUNCTION = 'random(1, 150000)')
ALTER Table Confidential
ALTER COLUMN CreditCard ADD MASKED WITH (FUNCTION='partial(1,"XXXX",2)')
ALTER Table Confidential
ALTER COLUMN Email ADD MASKED WITH (FUNCTION='email()')

I create now a user and add him to db_datareader role:

-- Create a user named TestDemo and add this user to the db_datareader role
USE DDM_TEST
go
CREATE USER TestDemo WITHOUT LOGIN
USE [DDM_TEST]
GO
ALTER ROLE [db_datareader] ADD MEMBER [TestDemo]
GO

Let’s try to visualize the Confidential table with my user:

Member of the db_datareader role are able to query the Confidential table but cannot see masked columns without masks.
Let’s try to add my user to the db_datawriter role and rerun my query:

Same, and it’s normal as db_datawriter cannot change read possibility, but the user is now able to insert data in the Condifendial table like this for example:

But, it cannot view in clear text data that it has inserted.
The only way to visualize data without masks is to be a member of the db_owner role:

Conclusion is clear, in order to be able to view masked columns user has to be member of the db_owner role in the database containing the table.
Happy masking

 

Cet article SQL Server 2016: Dynamic Data Masking and database role est apparu en premier sur Blog dbi services.

LISTAGG was a great feature introduced in 11g: put rows into line with a simple aggregate function. 12cR2 adds an overflow clause to it.

What happens when you have so many rows that the LISTAGG result is too long?

SQL> select listagg(rownum,',')within group(order by rownum) from xmltable('1 to 10000');
select listagg(rownum,',')within group(order by rownum) from xmltable('1 to 10000')
*
ERROR at line 1:
ORA-01489: result of string concatenation is too long


An error at runtime, and we don’t like runtime errors.

If you want to manage the overflow, it’s not easy: run a first query that sums the length and then calculate how much can fit

SQL> select v.*,4000-size_current from (
2 select n,
3 sum(length(n||',')) over(order by n rows between unbounded preceding and current row)-1 size_current,
4 sum(length(n||',')) over(order by n rows between unbounded preceding and 1 following)-1 size_next
5 from (select rownum n from xmltable('1 to 10000'))
6 ) v
7 where size_current between 4000-50 and 4000;
 
N SIZE_CURRENT SIZE_NEXT 4000-SIZE_CURRENT
---------- ------------ ---------- -----------------
1012 3952 3957 48
1013 3957 3962 43
1014 3962 3967 38
1015 3967 3972 33
1016 3972 3977 28
1017 3977 3982 23
1018 3982 3987 18
1019 3987 3992 13
1020 3992 3997 8
1021 3997 4002 3
 
9 rows selected.


Here you can see that values above 1020 will not fit in a VARCHAR2(4000).

In 12.2 you can manage the overflow in two ways

You can choose to raise a runtime error:

SQL> select listagg(rownum, ',' on overflow error)within group(order by rownum) from xmltable('1 to 10000');
select listagg(rownum, ',' on overflow error)within group(order by rownum) from xmltable('1 to 10000')
*
ERROR at line 1:
ORA-01489: result of string concatenation is too long


But you can also choose to truncate the result:

SQL> select listagg(rownum, ',' on overflow truncate '' without count)within group(order by rownum) from xmltable('1 to 10000');
 
LISTAGG(ROWNUM,','ONOVERFLOWTRUNCATE''WITHOUTCOUNT)WITHINGROUP(ORDERBYROWNUM)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,
103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,
178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,
253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,
328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,
403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,
478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,
553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,
628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,
703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,
778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,
853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,
928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,10
02,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013,1014,1015,1016,1017,1018,1019,1020,1021,


You may want to add some characters to show that it has been truncated:


SQL> select listagg(rownum, ',' on overflow truncate '...' without count)within group(order by rownum) from xmltable('1 to 10000');
 
LISTAGG(ROWNUM,','ONOVERFLOWTRUNCATE'...'WITHOUTCOUNT)WITHINGROUP(ORDERBYROWNUM)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,
103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,
178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,
253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,
328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,
403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,
478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,
553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,
628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,
703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,
778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,
853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,
928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,10
02,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013,1014,1015,1016,1017,1018,1019,1020,...


And you may even show the number of values that are not displayed:


SQL> select listagg(rownum, ',' on overflow truncate '...' with count)within group(order by rownum) from xmltable('1 to 10000');
 
LISTAGG(ROWNUM,','ONOVERFLOWTRUNCATE'...'WITHCOUNT)WITHINGROUP(ORDERBYROWNUM)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,
103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,
178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,
253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,
328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,
403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,
478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,
553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,
628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,
703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,
778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,
853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,
928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,10
02,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013,1014,1015,...(8985)


The nice thing is that the truncation is adapted to the information displayed:


SQL> select listagg(rownum, ',' on overflow truncate 'blah blah blah...' with count)within group(order by rownum) from xmltable('1 to 10000');
 
LISTAGG(ROWNUM,','ONOVERFLOWTRUNCATE'BLAHBLAHBLAH...'WITHCOUNT)WITHINGROUP(ORDERBYROWNUM)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,
103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,
178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,
253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,
328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,
403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,
478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,
553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,
628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,
703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,
778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,
853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,
928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,10
02,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,blah blah blah...(8988)


The “,blah blah blah…()” takes 20 characters, the count may take up to 24 characters, so the truncated value cannot be larger than 4000-20-24=3956. From the first query we run we see that we have to truncate after the value “2012”. There’s no dynamic evaluation of the count size.

If all the values fit, then it’s not truncated. In the first query we have seen that values up to 1021 takes 3997 characters:


SQL> select listagg(rownum, ',' on overflow truncate 'blah blah blah...' with count)within group(order by rownum) from xmltable('1 to 1021');
 
LISTAGG(ROWNUM,','ONOVERFLOWTRUNCATE'BLAHBLAHBLAH...'WITHCOUNT)WITHINGROUP(ORDERBYROWNUM)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,
103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,
178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,
253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,
328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,
403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,
478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,
553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,
628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,
703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,
778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,
853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,
928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000,1001,10
02,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013,1014,1015,1016,1017,1018,1019,1020,1021


In summary

After the delimiter string you can add:

• ON OVERFLOW ERROR which is the default. Same behavior as in previous releases.
• ON OVERFLOW TRUNCATE with a string that is added in case of truncation (default: ‘…’) and optionally WITH COUNT (or WITHOUT COUNT which is the default)

The full syntax is in the documentation

 

Cet article Oracle 12cR2 SQL new feature: LISTAGG overflow est apparu en premier sur Blog dbi services.

Je n’ai pas encore blogué sur le sujet mais il est temps de le faire. Cette année, aura lieu la première édition francophone des 24h du PASS  les 20 et 21 septembre 2016. L’idée est plutôt simple: proposer une série de 24 webinaires gratuits de 10h jusqu’à 22h (heure française)  pendant 2 jours. C’est l’occasion de recevoir et d’échanger les dernières informations autour de l’administration et du développement des bases de données, des nouvelles tendances côté Business Intelligence et du Cloud.

Qui dit événement Francophone dit aussi speakers de la communauté francophone avec du contenu en Français. Pour ma part, c’est avec plaisir que j’échangerais avec vous autour de 2 sujets: tempdb et bonnes pratiques ainsi que des columnstore et leur implication dans les nouvelles tendances d’architecture BI avec Thoi Dung TSP Microsoft Switzerland.

C’est aussi l’occasion de remercier les sponsors et Isabelle sans qui ce type d’événement n’aurait certainement pas lieu.

Aucune raisons de ne pas vous inscrire!

Au plaisir d’échanger avec vous au cours de cet événement!

 

Cet article Les 24 heures du PASS (24HOP) – édition francophone est apparu en premier sur Blog dbi services.

Venant de passer les deux derniers jours au siège d’Oracle pour le ACE Director briefing, j’en profite pour expliquer ce que représente le programme Oracle ACE car il y a peu de ressources en français.

On ne le sent pas toujours, mais Oracle est à l’écoute des utilisateurs. Oracle encourage les spécialiste de la communauté d’utilisateurs à partager et communiquer sur ses produits. Ce n’est pas pour faire simplement de la publicité commerciale, mais d’échanger et de faire connaitre la technologie. C’est l’OTN (Oracle Technology Network) qui gère le programme ACE.

Les titres de ACE Associate, ACE, et ACE Director sont une reconnaissance du travail effectué par les spécialistes au travers de différent canaux d’information: blogs, articles, présentation, organisation des groupes d’utilisateurs, écriture de livres techniques, etc.

Mais c’est aussi le moyen pour Oracle d’être à l’écoute des utilisateurs finaux, en dehors du réseau commercial. Les ACEs ont un contact privilégié avec les Product Manager pour tester les produits, parfois en beta, ouvrir et suivre les bugs rencontrés et faire un retour sur l’utilisation des fonctionnalités.

Les ACE directors se réunissent au siège juste avant l’Oracle Open World pour un briefing sur ce qui va être annoncé à l’Open World, et sur la Road Map des futures releases. Cela permet aux products managers de mieux présenter les nouveautés en fonction de ce qu’attendent les utilisateurs, et aux ACEs de pouvoir répondre aux questions des utilisateurs qui apprennent ces nouveautés.

Pour donner une idée du nombre de ACE Directors présents au siège, voici l’équipe:

Aujourd’hui, Oracle couvre un domaine beaucoup plus large que la base de donnée. Il y a du hardware, de la virtualisation, des systèmes d’exploitation, plusieurs bases de données, de la BI, ERP… L’objectif aujourd’hui d’Oracle est de s’imposer face à Amazon sur le IaaS, d’offrir la plus grande agilité en PaaS et une gamme très large en SaaS.

Mais heureusement, les bâtiments d’Oracle Corporation montrent toujours d’où ils sont partis: la base de donnée, stockée sur disque dur, toujours représentée par des cylindres rotatifs:

Aujourd’hui, les disques ne ressemblent plus à cela et de sont plus l’élément critique de l’IT car on ne dépend plus de la latence mécanique. Mais le symbole reste.

Si vous êtes à l’Oracle Open World cette année, n’hésitez pas à passer à l’OTN Lounge au Moscone South. Vous pourrez vous renseigner sur la communauté autour de la technologie Oracle, et sur le programme ACE.

Si vous ne maîtrisez pas l’anglais, pas de problème la Délégation Française propose plusieurs points de rencontre.

Et n’hésitez pas à venir voir ma session sur le Multitenant et j-interviens aussi pour parler Transportable Tablespace dans la session de l’EMEA User Group Community (EOUC)

 

Cet article Le programme Oracle ACE est apparu en premier sur Blog dbi services.

In this blog let’s talk about SQL Server and availability groups in standard Edition. I had some customer questions about existing limitations and this is a good opportunity to review them on this blog post. First of all, let’s say that Microsoft has already documented the restrictions here and from my side, I already written a blog post on the subject at the time of the CTP version of SQL Server 2016. In the meantime, some changes occurred and are now included in the RTM version.

As a reminder, the Standard Edition offers limited capabilities of availability groups and it tends to be a replacement of previous feature called mirroring. This is a good news for customers that may finally upgrade their old environment.

The first main limitation concerns the number of replicas capped to only 2 and with no possibility to use the secondary replica for Reporting and backups offloading as well. But we want to use a Standard Edition and it is supposed to be sold at a lower cost right?

Let’s just have a quick check by using the T-SQL script. Generally speaking, I’m not a big fan of the GUI! So if I try to create an availability group with 3 replicas, I will obviously face the following error message:

Msg 35233, Level 16, State 0, Line 2
Cannot create an availability group containing 3 availability replica(s). 
The maximum number of availability replicas in an availability group  with (basic) is 2. 
Reenter your CREATE AVAILABILITY GROUP command specifying fewer availability replicas.

Let’s try to use a secondary replica as read-only replica (ALLOW_CONNECTIONS = ALL)

-- primary replica
CREATE AVAILABILITY GROUP [testGrpStd]   
FOR  
REPLICA ON
N'WIN20121SQL16\SQL16STD'
WITH (ENDPOINT_URL = N'TCP://WIN20121SQL16.dbi-services.test:5023',  
    FAILOVER_MODE = AUTOMATIC,  
    AVAILABILITY_MODE = SYNCHRONOUS_COMMIT,   
    BACKUP_PRIORITY = 50,   
    SECONDARY_ROLE(ALLOW_CONNECTIONS = ALL),   
    SEEDING_MODE = MANUAL)
,
N'WIN20124SQL16\SQL16STD'
WITH (ENDPOINT_URL = N'TCP://WIN20124SQL16.dbi-services.test:5022',   
    FAILOVER_MODE = AUTOMATIC,   
    AVAILABILITY_MODE = SYNCHRONOUS_COMMIT,   
    BACKUP_PRIORITY = 50,   
    SECONDARY_ROLE(ALLOW_CONNECTIONS = ALL),   
    SEEDING_MODE = MANUAL);   
GO

Well another error message I got here:

Msg 41199, Level 16, State 8, Line 2
The specified command is invalid because the Always On Availability Groups allow_connections feature
is not supported by this edition of SQL Server. For information about features supported by the editions
of SQL Server, see SQL Server Books Online.

However, I noticed a big change compared to my first test with a CTP version concerning the possibility to add a listener to my availability group. From my point of view, this is a very good improvement compared to the mirroring feature because no changes will be required at the application layer with additional options at the connection string level. Let me prove it with the following script:

USE [master]
GO
ALTER AVAILABILITY GROUP [testGrpStd]
ADD LISTENER N'Test-GrpSTD' (
WITH IP
((N'192.168.5.122', N'255.255.255.0')
)
, PORT=1433);
GO

We can check the listener creation by using DMVs to get the listener configuration as shown below:

According to my discussions with some customers at our last SQL Server 2016 event, availability groups in Standard Edition may also suggest that more complex infrastructures like multi-subnet availability groups or new special features like direct seeding will not be supported. A first look at the Microsoft documentation doesn’t provide any clues. You can argue that the Microsoft documentation is black-list oriented and if it is not written explicitly in the documentation it should work and you are probably right. But you know, I’m curious and I was interesting to check myself on my lab environment!

For the both suppositions, I can confirm that I didn’t face any issue when creating an availability group with a different setup scenario on the top of multi-subnet WSFC or when using direct seeding. Here the script used to create my availability group with a listener and two IP addresses on different subnet. I also have enabled the direct seeding feature by configuring the SEEDING_MODE parameter to AUTOMATIC as shown below.

-- Availability groups with SEEDING_MODE = AUTOMATIC
CREATE AVAILABILITY GROUP [testGrpStd]   
FOR  
REPLICA ON
N'WIN20121SQL16\SQL16STD'
WITH (ENDPOINT_URL = N'TCP://WIN20121SQL16.dbi-services.test:5023',  
    FAILOVER_MODE = AUTOMATIC,  
    AVAILABILITY_MODE = SYNCHRONOUS_COMMIT,   
    BACKUP_PRIORITY = 50,   
    SECONDARY_ROLE(ALLOW_CONNECTIONS = NO),   
    SEEDING_MODE = AUTOMATIC)
,
N'WIN20124SQL16\SQL16STD'
WITH (ENDPOINT_URL = N'TCP://WIN20124SQL16.dbi-services.test:5022',   
    FAILOVER_MODE = AUTOMATIC,   
    AVAILABILITY_MODE = SYNCHRONOUS_COMMIT,   
    BACKUP_PRIORITY = 50,   
    SECONDARY_ROLE(ALLOW_CONNECTIONS = NO),   
    SEEDING_MODE = AUTOMATIC);   
GO

-- Listener with two IP addresses on a different subnet 
ALTER AVAILABILITY GROUP [testGrpStd]
ADD LISTENER N'Test-GrpSTD' (
WITH IP
((N'192.168.5.122', N'255.255.255.0'),
 (N'192.168.50.122', N'255.255.255.0')
)
, PORT=1433);
GO

Now let’s have a look at the availability group configuration and direct seeding parameter value

Here the listener configuration retrieved from the sys.availability_group_listeners DMV:

Let’s take this opportunity to change the replication type to ASYNCHRONOUS. In fact, I had in mind the mirroring feature when using the asynchronous replication that was only available with Enterprise edition. This is another interesting point and now we may benefit from both asynchronous and synchronous replication mode regardless the edition. By the way this feature is clearly documented in the BOL.

Finally let’s check if direct seeding works as expected. If you don’t know what direct seeding is please refer to my previous blog. Just as reminder, we must first configure direct seeding on the secondary by granting the correct permission to the availability group itself.

ALTER AVAILABILITY GROUP [testGrpStd] GRANT CREATE ANY DATABASE 
GO

Here we go. Let’s finally add the database to my existing availability and let’s see if direct seeding comes into play

ALTER AVAILABILITY GROUP testGrpStd ADD DATABASE test_db;  
GO

To get data from direct seeding session states we may use DMVs like sys.dm_hadr_automatic_seeding and sys.dm_hadr_physical_seeding_stats as well.

Sounds good right?

Bottom line

Basic availability groups feature is shipped with limited features. Yes, but in a meantime it will still respond to a large number of customer scenarios where we have to find a balance between high availability options and costs. Referring to some discussions I had with some customers, they don’t need special features provided by availability groups like readable secondaries or offloading backups. They just want to benefit from high availability for only some critical applications. I’m looking forward to see basic availability groups at customer shops!

 

 

 

 

Cet article SQL Server 2016 : Basic availability groups may fit to your HA needs est apparu en premier sur Blog dbi services.

As you already might know dbi (on a technical level) is organized into several technology divisions. Traditionally there is one for Oracle, one for Microsoft and one for Middleware products. Almost a year ago a new technology division was born to reflect the new requirements we see on the market. This does not mean that we did not provide expertise in these areas before but the goal was to more clearly organize ourself for being able to rapidly adopt new technologies and provide the best expertise for our current and future customers. In this post I’ll take a look at our Open Infrastructure Technology Division. What is it about, what do we believe in and what you can expect now and in the future.

To start with: What do we call a technology division? As the name already adumbrates it is all about technology. You could also say: The technology division are the heart of dbi. This is where people work on the different technologies, organize technical events, do researching, define and plan new workshops, adopt new products and have lots of fun. Each of these technology divisions is led by a so called technology leader who is responsible for his technology division. Currently dbi supports four of these divisions which reflect the areas we work in:

On the top there is Hervé who is our CTO and then we have the four technology divisions:

• We have Franck who is responsible for all aspects around the Oracle database
• We have Stéphane who is responsible for the Microsoft stuff
• We have Gérard who is responsible for everything around the middleware products we support
• And finally we have the Open Infrastructure Technology Division which I am happy to represent

A very important point to notice here is that each of these divisions is cross connected to every other. We are not working in isolated silos but do work together wherever we can. Nowadays you can never be sure what happens and things have recently happened you never thought would be possible in the past, e.g.

• Microsoft and Red Hat to deliver new standard for enterprise cloud experiences
• PowerShell on Linux and Open Source!
• SQL Server on Linux

… just to name a few. Do you know if you need a SQL Server expert on Linux tomorrow? Are you running Oracle on Windows? Are you planning to run Docker on Windows? These are just a few examples where you might need expertise which goes beyond the traditional “I only do Windows” or “I only do Oracle” way of working. This is what the technology divisions are there for: Build expertise inside the divisions but even more important build a kind of “backbone” where everyone can get help from others (inside and outside of dbi). Share what you learned, be open, be communicative, be mindful and have an open eye on what is going on around you. No matter which technology division you take: All of them share their knowledge by writing blogs, attending, organizing and speaking at events (e.g. DOAG 2016, Oracle Open World 2016, IT-Tage 2016, SWISS PGDay, PASS SQLSaturdays and many more), writing articles, creating hands-on workshops and even come together twice a year for exchanging knowledge across the technology divisions.

So far for the overview (which is far longer that it intended to be, sorry). Lets focus on the Open Infrastructure Division from now on. Probably the most important point in any division is what it stands for, so what do we stand for? As you can see from the name the word “Open” plays a central role. We do not only believe in open source software but even more important believe that being and thinking open is key to success. There are plenty of wonderful open source projects out there, each of them having an active community and each of them supporting business critical applications. Our idea is not to favor one over another but rather selecting the right technology for the right requirement. This might range from one specific product to a whole set of products. This could even result in extending (or interfacing) a proprietary solution by open source solutions when it makes sense (remember the cross connected divisions described above).

On the other hand we can not support the whole open source world because this is just not possible so we have to select a kind of technology set we want to focus on (more on that later). This set is and will be changing over time, we are absolutely aware of that. New technologies will come in, others will go out and some will stay. That’s the way of life. Important for us is the “Open Infrastructure” because when things change you need to adopt. When you keep your infrastructure open it is much more easy to adopt than when you have to adopt your closed systems. When you focus on real open standards, open formats and open software you are free to decide in which direction you want to go and even if it was the wrong decision you are not on a …

… you are free to adjust the direction This is more or less what we believe in and work on every day: Making infrastructures more open, easier to maintain, easier to adapt, faster to profit from and more fun to work with. Yes, work can be fun when you have the right tools and the right people to work with.

Going deeper into our division what do we actually provide? We had various internal discussion about that and it was not easy to come to a final conclusion. Indeed there is no final set or conclusion but we do provide what we call a “core” set. This are our core technologies we currently work on, provide best practices, provide trainings for (some), provide consulting (all), provide SLAs (some), implement (all) and do reviews or feasibility studies (all). So, finally here they are (bottom up):

On the Linux level:

On the rdbms level:

On the NoSQL level:

On the provisioning and deployment level:

On the monitoring level:

On the DevOps and OpenStack level:

This are quite a few but not too much technologies. As already stated somewhere above we do not provide everything for every product but we are constantly extending our knowledge and best practices so that products might be fully supported by us in the future which are not today. Other products we are working on are not even listed above (e.g. the E(astic search) L(ogstash) K(ibana) stack). Believe me: It is really hard to select the right tools for the right job: This is what we are here for.

 

Cet article The dbi Open Infrastructure Technology Division est apparu en premier sur Blog dbi services.

During the execution of a SQL statement, you cannot guess how many times an operation, a predicate, or a function will be executed. This depends on the execution plan, on some caching at execution, and some other execution time decisions. Here is an example where result cache may bring some overhead by calling a function multiple times.

Here is my function:
SQL> create or replace function F return number is
2 begin
3 dbms_lock.sleep(5);
4 dbms_output.put_line('Hello World');
5 return 255;
6 end;
7 /
Function created.
The function displays ‘Hello World’ so that I can check how many times it is executed (I’ve set serveroutput on).

Obviously, on a one row table, it is called only once:
SQL> select f from dual;
 
F
----------
255
 
Hello World

Query result cache miss

I’ll run now the same query but with the result cache hint. The first execution will have to execute the query because the cache is empty at that point:

SQL> exec dbms_result_cache.flush;
PL/SQL procedure successfully completed.
 
SQL> select /*+ result_cache */ f from dual;
 
F
----------
255
 
Hello World
Hello World

Here is what I wanted to show: ‘Hello World’ is displayed two times instead of one. If your function is an expensive one, then the first execution, or every cache miss, will have a performance overhead.

Query result cache hit

Now that the result is in the cache:

SQL> select id, type, status, name from v$result_cache_objects;
 
ID TYPE STATUS NAME
---------- ---------- --------- ------------------------------------------------------------
33 Dependency Published DEMO.F
34 Result Published select /*+ result_cache */ f from dual

and the table has not changed (it’s DUAL here :; ) further executions do not call the function anymore, which is the expected result.

SQL> select /*+ result_cache */ f from dual ;
 
F
----------
255

Bug or not?

Bug 21484570 has been opened for that and closed as ‘Not a bug’. There is no guarantee that the function is evaluated once, twice, more or never.
Ok, why not. That’s an implementation decision. Just think about it if you want to workaround an expensive function called for each row, then query result cache may not be the right solution (except if all tables are static and you always have cache hits).

Note that if the function is declared as deterministic, it is executed only once.

You can workaround the issue by using result cache at function level (in place, or in addition to query result cache if you need it).

SQL> create or replace function F return number RESULT_CACHE is
2 begin
3 dbms_lock.sleep(5);
4 dbms_output.put_line('Hello World');
5 return 255;
6 end;
7 /
Function created.
 
SQL> select /*+ result_cache */ f from dual;
 
F
----------
255
 
Hello World
 
SQL> select id, type, status, name from v$result_cache_objects;
 
ID TYPE STATUS NAME
---------- ---------- --------- ------------------------------------------------------------
64 Dependency Published DEMO.F
66 Result Published "DEMO"."F"::8."F"#e17d780a3c3eae3d #1
65 Result Published select /*+ result_cache */ f from dual

So, not a big problem. Just something to know. And anyway, the right design is NOT to call a function for each row because it’s not scalable. Pipeline functions should be used for that.

 

Cet article Result cache side effects on number of calls est apparu en premier sur Blog dbi services.

In this article we are going to talk about sharding in PostgreSQL. What is sharding, Sharding is like partitioning. The difference is that with traditional partioning, partitions are stored in the same database while sharding shards (partitions) are stored in different servers.
Below is an example of sharding configuration we will use for our demonstration

PostgreSQL does not provide built-in tool for sharding. We will use citus  which extends PostgreSQL capability to do sharding and replication.
We will use 3 servers
pgshard0: 192.168.1.50
pgshard1: 192.168.1.51
pgshard2: 192.168.1.52
First let’s install PostgreSQL + citus extension on all servers (pgshard0, pgshard1, pgshard2). We suppose of course that network is configured so that all server can communicate
[root@pgshard0 ~]# yum install -y https://download.postgresql.org/pub/repos/yum/9.5/redhat/rhel-7-x86_64/pgdg-oraclelinux95-9.5-2.noarch.rpm
[root@pgshard0 ~]# yum install -y citus_95.x86_64
Now let’s  to initialize a new database system on all servers (pgshard0, pgshard1, pgshard2)
[root@pgshard0 ~]# /usr/pgsql-9.5/bin/postgresql95-setup initdb
Initializing database ... OK
To load citus extension we have to edit the /var/lib/pgsql/9.5/data/postgresql.conf   file and add the following line
shared_preload_libraries = ‘citus’
[root@pgshard0 data]# grep shared_preload_libraries /var/lib/pgsql/9.5/data/postgresql.conf
#shared_preload_libraries = '' # (change requires restart)
shared_preload_libraries = 'citus'
[root@pgshard0 data]#
To allow postgreSQL connection between servers we have to configure two configuration files /var/lib/pgsql/9.5/data/postgresql.conf  and /var/lib/pgsql/9.5/data/pg_hba.conf
[root@pgshard0 data]# grep listen postgresql.conf
listen_addresses = '*' # what IP address(es) to listen on;
[root@pgshard0 data]#
[root@pgshard0 data]# grep trust pg_hba.conf
# METHOD can be "trust", "reject", "md5", "password", "gss", "sspi",
host all all 127.0.0.1/32 trust
host all all 192.168.1.0/24 trust
host all all ::1/128 trust
[root@pgshard0 data]#

Let’s now start database on all servers (pgshard0, pgshard1, pgshard2)

[root@pgshard0 data]# service postgresql-9.5 start
Redirecting to /bin/systemctl start postgresql-9.5.service
[root@pgshard0 data]#

 We need to inform the master (pgshard0) about its workers (pgshard1 and pgshard2). For this we have to create a configuration file pg_worker_list.conf  like this

[root@pgshard0 data]# pwd
/var/lib/pgsql/9.5/data
[root@pgshard0 data]# cat pg_worker_list.conf
pgshard1 5432
pgshard2 5432
[root@pgshard0 data]#

Let’s now reload the master pgshard0  to take into account the modification

[root@pgshard0 ~]# service postgresql-9.5 reload
Redirecting to /bin/systemctl reload postgresql-9.5.service
[root@pgshard0 ~]#

Very important:  we must create citus extension on both servers

postgres=# create extension citus;
CREATE EXTENSION
postgres=# \dx
List of installed extensions
Name | Version | Schema | Description
---------+---------+------------+------------------------------
citus | 5.2-1 | pg_catalog | Citus distributed database
plpgsql | 1.0 | pg_catalog | PL/pgSQL procedural language
(2 rows)

The last step before the sharding is now to verify that the master is ready. This SELECT command we will  run in the psql shell should output the worker nodes mentioned in the pg_worker_list.conf file.

postgres=# SELECT * FROM master_get_active_worker_nodes();
node_name | node_port
-----------+-----------
pgshard2 | 5432
pgshard1 | 5432
(2 rows)
postgres=#

Every thing is going fine until now, so we can create on the master the table to be sharded. Let’s say table sales

postgres=# CREATE TABLE sales
postgres-# (deptno int not null,
postgres(# deptname varchar(20),
postgres(# total_amount int,
postgres(# CONSTRAINT pk_sales PRIMARY KEY (deptno)) ;
CREATE TABLE

We need have inform Citus that data of table sales will be distributed among pghard1 and pgshard2. In our case we choose a hash distribution.

postgres=# SELECT master_create_distributed_table('sales', 'deptno', 'hash');
master_create_distributed_table
---------------------------------
(1 row)

In our example we are going to create one shard on each worker. We will  Specify
the table name :  sales
total shard count : 2
replication factor :  1  –No replication
postgres=# SELECT master_create_worker_shards('sales', 2, 1);
master_create_worker_shards
-----------------------------
(1 row)
postgres=#


And guys it’s all. Sharding is done. Connecting to pgshard1 and pgshard2 we can verify that shards were created with the same structure than the base table.

[postgres@pgshard1 bin]$ psql -c "\dt"
List of relations
Schema | Name | Type | Owner
--------+--------------+-------+----------
public | sales_102026 | table | postgres
(1 row)

[postgres@pgshard2 ~]$ psql -c "\dt"
List of relations
Schema | Name | Type | Owner
--------+--------------+-------+----------
public | sales_102027 | table | postgres
(1 row)
Now let’s insert some rows in the table from the master
postgres=# insert into sales (deptno,deptname,total_amount) values (1,'french_dept',10000);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (2,'german_dept',15000);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (3,'china_dept',21000);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (4,'gambia_dept',8750);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (5,'japan_dept',12010);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (6,'china_dept',35000);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (7,'nigeria_dept',10000);
INSERT 0 1
postgres=# insert into sales (deptno,deptname,total_amount) values (8,'senegal_dept',33000);
INSERT 0 1
postgres=#

We can see that data are distributed between pgshard1 and pgshard2

[postgres@pgshard1 bin]$ ./psql
psql (9.5.4)
Type "help" for help.
postgres=# select * from sales_102026;
deptno | deptname | total_amount
--------+--------------+--------------
1 | french_dept | 10000
3 | india_dept | 21000
4 | gambia_dept | 8750
5 | japan_dept | 12010
7 | nigeria_dept | 10000
8 | senegal_dept | 33000
(6 rows)

[postgres@pgshard2 bin]$ ./psql
psql (9.5.4)
Type "help" for help.
postgres=# select * from sales_102027;
deptno | deptname | total_amount
--------+-------------+--------------
2 | german_dept | 15000
6 | china_dept | 35000
(2 rows)

If we do an explain from the master pgshard0, we note that query is routed to different shard depending of data
postgres=# explain verbose select * from sales where deptno=5;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------
Distributed Query
Executor: Router
Task Count: 1
Tasks Shown: All
-> Task
Node: host=pgshard1 port=5432 dbname=postgres
-> Index Scan using pk_sales_102026 on public.sales_102026 sales (cost=0.15..8.17 rows=1 width=66)
Output: deptno, deptname, total_amount
Index Cond: (sales.deptno = 5)
(9 rows)

postgres=# explain verbose select * from sales where deptno=6;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------
Distributed Query
Executor: Router
Task Count: 1
Tasks Shown: All
-> Task
Node: host=pgshard2 port=5432 dbname=postgres
-> Index Scan using pk_sales_102027 on public.sales_102027 sales (cost=0.15..8.17 rows=1 width=66)
Output: deptno, deptname, total_amount
Index Cond: (sales.deptno = 6)
(9 rows)

Conclusion:
In this article we show that PostgreSQL allows to do many interesting things. Use of extensions can considerably extend PostgreSQL capability

 

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