asynchronous global index maintenance for drop and truncate partition - oracle

We have a very large partitioned table that needs to drop partition periodically. The business system needs 7*24 hours of operation.
We use global index.
From the following article, we know that Oracle supports asynchronous index update.
https://oracle-base.com/articles/12c/asynchronous-global-index-maintenance-for-drop-and-truncate-partition-12cr1
But : "The actual index maintenance is performed at a later time"\
Does it affect the normal business when it is actually executed.( Query/Insert/Update/Delete )

No it doesn't, as you can read here (I supposed you are running 12.1 as you didn't specify database version and you linked 12.1 documentation).
The parts that are of interest to you are the following:
The partitions of tables containing local indexes are locked to prevent DML operations against the affect table partitions, except for an ONLINE MOVE operation. However, unlike the index maintenance for local indexes, any global index is still fully available for DML operations and does not affect the online availability of the OLTP system.
[...]
For example, dropping an old partition is semantically equivalent to deleting all the records of the old partition using the SQL DELETE statement. In the DML case, all index entries of the deleted data set have to be removed from any global index as a standard index maintenance operation, which does not affect the availability of an index for SELECT and DML operations.

Related

Removing bloat from greenplum table

I have created some tables in Greenplum, performing insert update and delete operation. Regularly I am also performing vacuum operation. I Found bloat in it. Found solution to remove bloat https://discuss.pivotal.io/hc/en-us/articles/206578327-What-are-the-different-option-to-remove-bloat-from-a-table
However, if I truncate the table and reinsert the data, it removes bloat. Is it good practice to truncate the data from the table?
If you are performing UPDATE and DELETE statements on a heap table (default storage) and running VACUUM regularly, you will get some bloat by design. Heap storage, which is similar to the default PostgreSQL storage mechanism, provides read consistency using Multi-Version Concurrency Control (MVCC).
When you UPDATE or DELETE a record, the old value is still in the table and is able to be read by transactions that are still inflight and started before you issued the UPDATE or DELETE command. This provides the read consistency to the table.
When you execute a VACUUM statement, the database will mark the stale rows as available to be overwritten. It doesn't shrink the files. It just marks rows so they can be overwritten. The next time you execute an INSERT or UPDATE, the stale rows are now able to be used for the new data.
So if you UPDATE or DELETE 10% of a table between running VACUUM, you will probably have about 10% bloat.
Greenplum also has Append-Optimized (AO) storage which doesn't use MVCC and uses a visibility map instead. The files are bit smaller too so you should get better performance. The stale rows are hidden with the visibility map and VACUUM won't do anything until you hit the gp_appendonly_compaction_threshold percentage. The default is 10%. When you have 10% bloat in an AO table and execute VACUUM, the table will automatically get rebuilt for you.
Append-Optimized is called "appendonly" for backwards compatibility reasons but it does allow UPDATE and DELETE. Here is an example of an AO table:
CREATE TABLE sales
(txn_id int, qty int, date date)
WITH (appendonly=true)
DISTRIBUTED BY (txn_id);
Instead of truncate it is better to use drop the table, create the table and then insert the data.

Is okay to create indexes on a table while insertion

Is it okay to create an index on a table while , lets say when are there some tasks which creates some new rows into the table at the same time?? Would there be any locking issues???
EX: FEEDBACK TABLE --> creating an index on (Name, feedbackrule) while there are any inserts happening simultaneously , is this BAD?? if so what.
I'm assuming, Oracle will just not use this index when the inserts are happening, later this will be used.
Normally, creating an index requires locking the table, so all the DML operations would block; and if there are active transactions on the table when you initiate the index creation, you'd likely get the error "ORA-00054: resource busy and acquire with NOWAIT specified or timeout expired".
If the table is small, this may not be much of an issue - transactions would just be blocked for a few moments. But if it is very large it would be a bad idea to try creating an index while the table is in use.
However, if you using Enterprise Edition, you can add the ONLINE keyword to your CREATE INDEX statement, which will allow transactions to proceed against the table while the index is building. It may still cause slower performance.

In Oracle, what dictionary table tells me the "store in" value for partitioned indexes?

We are running Oracle 11g and have some partitioned tables. I am trying to write an automated process to script out the indexes on these tables. (Basically when we do bulk loads, we want to drop all the indexes beforehand and recreate them afterward.)
The problem I have is knowing how to script out the partitioned indexes. Some are created with "LOCAL STORE IN (tablespacename)" and others just with "LOCAL" (which stores index extents in the same partition as the data). In either case, dba_indexes.tablespace_name is null, and I have having a heck of a time scripting out the two different cases correctly.
I know I can simply re-run the original DDL to recreate the indexes, but multiple parts of the organization can make changes, and there would be less risk if the loader tool could be self-contained and simply rebuild whatever was there to begin with.
I can query dba_ind_subpartitions, and if the tablespace_name values for every subpartition all match, then I can assume/infer that I should STORE IN that tablespace name. But, if the table is in a small single-partition state (e.g. newly created or just after archival), then the ones created with just LOCAL also match this test, so this is also not a perfect way of telling them apart.
I can compare the names of the index subpartition tablespaces to the data table partition tablespaces, and if they match, then I can assume/infer that those should be created with just LOCAL. But, that drags a bunch of extra tables into my query and makes it really hard to read, so I am worried about maintainability going forward. Plus, it just seems like a kludge.
It seems like there should be someplace in Oracle's data dictionaries where it is simply keeping track of this, and where I can just directly look it up instead of having to do a bunch of math and rely on assumptions. But, I have done a good deal of digging and haven't yet found it. So, any help would be much appreciated.
Although an insert alone is faster without the presence of indexes, have you benchmarked a load into tables with indexes enabled and established that it is slower than disabling (more robust than dropping!) and rebuilding them?
When you direct path insert into a table with indexes, Oracle optimises the index maintenance process by creating temporary segments to hold just the data required for the index builds. This generally allows the index maintenance to scan much smaller segments than otherwise required -- the temp segments plus the existing indexes.
Well, as jonearles describes, the dbms_metadata package is the way to generate DDL for existing objects.
But, it seems to me, this is more work than is required for what you're trying to achieve. If this is all for loading data, I recommend you simply alter the indexes to be unusable, set 'skip_unusable_indexes=true', do the data load, and the rebuild the indexes.
This should achieve what you want, without having to drop and re-create the indexes.
DBMS_METADATA.GET_DDL is easier than querying the data dictionary:
--Sample table and index.
create table test1(a number);
create index test1_idx on test1(a);
--Store the DDL, drop the index, then re-create it.
declare
ddl_before clob;
begin
ddl_before := dbms_metadata.get_ddl('INDEX', 'TEST1_IDX');
execute immediate 'drop index test1_idx';
--Do some processing here.
execute immediate ddl_before;
end;
/

Oracle PL/SQL Table memory usage vs temporary tables

I am incrementally pulling records from a Web Service. I need to set the status of any records in our local table that were not returned by the Web Service to 'DELETED';
I had intended to store the complete list of record IDs in a PL/SQL table and then perform a single UPDATE statement based on that.
I now estimate the memory usage of the record set to be ~615MB. How does the memory footprint of a PL/SQL table compare to using a global temporary table instead? Would it use a different part of Oracle's memory, PGA vs SGA for instance?
Performance isn't a major concern because this nightly job already runs in Production in an acceptable amount of time. I don't believe adding the 'DELETED' status piece will increase the run duration to affect users.
A global temporary table would not use memory in that way. It stores the values in a temporary segment to which only your session has access, and which is dropped when no longer needed.
Have you considered what happens if your session disconnects? In either method you lose the values you have accumulated. You might like to just use a regular table.

PostgreSQL temporary tables

I need to perform a query 2.5 million times. This query generates some rows which I need to AVG(column) and then use this AVG to filter the table from all values below average. I then need to INSERT these filtered results into a table.
The only way to do such a thing with reasonable efficiency, seems to be by creating a TEMPORARY TABLE for each query-postmaster python-thread. I am just hoping these TEMPORARY TABLEs will not be persisted to hard drive (at all) and will remain in memory (RAM), unless they are out of working memory, of course.
I would like to know if a TEMPORARY TABLE will incur disk writes (which would interfere with the INSERTS, i.e. slow to whole process down)
Please note that, in Postgres, the default behaviour for temporary tables is that they are not automatically dropped, and data is persisted on commit. See ON COMMIT.
Temporary table are, however, dropped at the end of a database session:
Temporary tables are automatically dropped at the end of a session, or
optionally at the end of the current transaction.
There are multiple considerations you have to take into account:
If you do want to explicitly DROP a temporary table at the end of a transaction, create it with the CREATE TEMPORARY TABLE ... ON COMMIT DROP syntax.
In the presence of connection pooling, a database session may span multiple client sessions; to avoid clashes in CREATE, you should drop your temporary tables -- either prior to returning a connection to the pool (e.g. by doing everything inside a transaction and using the ON COMMIT DROP creation syntax), or on an as-needed basis (by preceding any CREATE TEMPORARY TABLE statement with a corresponding DROP TABLE IF EXISTS, which has the advantage of also working outside transactions e.g. if the connection is used in auto-commit mode.)
While the temporary table is in use, how much of it will fit in memory before overflowing on to disk? See the temp_buffers option in postgresql.conf
Anything else I should worry about when working often with temp tables? A vacuum is recommended after you have DROPped temporary tables, to clean up any dead tuples from the catalog. Postgres will automatically vacuum every 3 minutes or so for you when using the default settings (auto_vacuum).
Also, unrelated to your question (but possibly related to your project): keep in mind that, if you have to run queries against a temp table after you have populated it, then it is a good idea to create appropriate indices and issue an ANALYZE on the temp table in question after you're done inserting into it. By default, the cost based optimizer will assume that a newly created the temp table has ~1000 rows and this may result in poor performance should the temp table actually contain millions of rows.
Temporary tables provide only one guarantee - they are dropped at the end of the session. For a small table you'll probably have most of your data in the backing store. For a large table I guarantee that data will be flushed to disk periodically as the database engine needs more working space for other requests.
EDIT:
If you're absolutely in need of RAM-only temporary tables you can create a table space for your database on a RAM disk (/dev/shm works). This reduces the amount of disk IO, but beware that it is currently not possible to do this without a physical disk write; the DB engine will flush the table list to stable storage when you create the temporary table.

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