RE: Hash to range partition

Well, let's see:

Is there already a date column on the table?

Is it the "born-on" date?

So picking the 90+ percent edge case of business data that has "yes" to both of those, is it also true that there is an offset date, and "age" if you will after which such rows can never again be modified?

Once again I'll go with the edge case (perhaps only 80% of the earlier 90+%) that is true.

Then:

Create a very dense table structure (0 percent free) and find the shortest key that is tied for query parameter.

Partition by that date column, whether by hour, day, week, month depending on what makes sense for queries.

Insert into those partitions using the filter for just the rows for each partition and order by that column (or columns) for all the periods that have not yet become quiescent.

Then set up a the rest of the partitions at a percent free that will accommodate likely updates for the "young" partitions and copy them in.

Now, your monthly maintenance (or whatever period you are partitioned on) becomes copy out the "became quiescent" partitions to percent free 0 storage with the same order by, and swap them back in.

Betcha everything runs faster for just a wee bit of trouble that is NOT an extra work forever treadmill.

Good luck,

mwf
-----Original Message-----
From: oracle-l-bounce_at_freelists.org [mailto:oracle-l-bounce_at_freelists.org] On Behalf Of Mladen Gogala Sent: Thursday, July 30, 2020 6:59 PM
To: oracle-l_at_freelists.org
Subject: Re: Hash to range partition

Hi Ram!

There are only 2 things I can think of:

1. Create new table, do insert /* +APPEND */ into new_tab select /*+ parallel(16) */ from old_table;
2. Use DBMS_REDEFINITION

Personally, I would use the first method, if possible.

Regards

On 7/30/20 6:16 PM, Ram Raman wrote:
> All,
>
> We have a 1.4B row table that is hash partitioned by a key (ID). The
> key is increasing monotonically and seems to be coming from a
> sequence. The loads happen nightly and those are the only time the
> table is inserted to; during the day time only SELECTs run against the
> table.
>
> The table has 4 indexes on it, including one on the ID column. None of
> the indexes are partitioned (!)
>
> table t:
> --------
>
> ID NUMBER(16)
> ...
> EFFDT DATE
> ..
>
> Unique Index on ID column. Two other single column indexes on 2 number
> columns and one single column index on a date column.
>
> Queries that run in the day time typically access past several months
> of data from the table by the ID key mostly. It is accessed via other
> columns as well, but that is less than 20% of the time. There are
> about 10M rows per month and we have 32 hash partitions. No INSERTS in
> the day time.
>
> Since the load is happening nightly and there are only queries in the
> day time, I am considering testing out range partitioning the table
> rather than hash partitioning. It seems hash partitioning is
> recommended for keys based on sequences to avoid index contention
> during inserts. However, with the hash based approach the queries are
> scanning all partitions having to go through all 1.4B rows for a few
> months of records. If I go with range partitioning (one per month) on
> the ID key and if the queries access past few months of data only, I
> feel we can see a substantial performance improvement with queries
> only having to visit a fraction of the partitions and rows.
> I am also planning on creating a locally partitioned index on the ID
> column and also partitioned indexes on the other 3 columns as well.
> Not sure if it will increase the load time. One option for the indexes
> is that the locally partitioned index will have the new partition
> created as needed and the remaining 3 indexes dropped and rebuilt
> nightly. Will this be faster than the index getting updated during the
> daily loads?
>
> Can the listers share their thoughts on moving to range partition and
> indexes during load.
> Ram.
> --
>

--
Mladen Gogala
Database Consultant
Tel: (347) 321-1217

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