– Erwin Brandstetter Dec 9 at 21:46 (thank you -E). Once you’ve gotten the majority of your bloat issues cleaned up after your first few times running the script and see how bad things may be, bloat shouldn’t get out of hand that quickly that you need to run it that often. il y a 3 années et 6 mois. If "ma" is supposed to be "maxalign", then this code is broken because it only reports mingw32 as 8, all others as 4, which is wrong. Different types of indexes have Different purposes, for example, the B-tree index was effectively used when a query involves the Range and equality operators and the hash index is effectively used when the equality pgconf.eu, I added these links to the following In this version of the query, I am computing and adding the headers length of Functionally, both are the same as far as PostgreSQL is concerned. DROP CONSTRAINT […] call, which will require an exclusive lock, just like the RENAME above. It’s gotten pretty stable over the last year or so, but just seeing some of the bugs that were encountered with it previously, I use it as a last resort for bloat removal. I’d say a goal is to always try and stay below 75% disk usage either by archiving and/or pruning old data that’s no longer needed. An index field is Unlike the query from check_postgres, this one focus only on BTree index its disk layout. Dalibo, these Btree bloat estimation queries keeps challenging me occasionally However, I felt that we needed several additional changes before the query is ready for me to use in our internal monitoring utilities, and thought I'd post our version here. Since I initially wrote my blog post, I’ve had some great feedback from people using pg_bloat_check.py already. This is the second part of my blog “ My Favorite PostgreSQL Extensions” wherein I had introduced you to two PostgreSQL extensions, postgres_fdw and pg_partman. For Btree indexes, pick the correct query here depending to your PostgreSQL version. However, that final ALTER INDEX call can block other sessions coming in that try to use the given table. A few weeks ago, I published a query to estimate index bloat. reinsertion into the bloated V4 index reduces the bloating (last point in the expectation list). And if your database is of any reasonably large size, and you regularly do updates & deletes, bloat will be an issue at some point. Same for running at the DATABASE level, although if you’re running 9.5+, it did introduce parallel vacuuming to the vacuumdb console command, which would be much more efficient. This can also be handy when you are very low on disk space. In this case it’s a very easy index definition, but when you start getting into some really complicated functional or partial indexes, having a definition you can copy-n-paste is a lot safer. I will NOT publish your email address. I have used table_bloat_check.sql and index_bloat_check.sql to identify table and index bloat respectively. This will take an exclusive lock on the table (blocks all reads and writes) and completely rebuild the table to new underlying files on disk. So add around 15% to arrive at the actual minimum size. However, the equivalent database table is 548MB. I also made note of the fact that this script isn’t something that’s made for real-time monitoring of bloat status. It’s been almost a year now that I wrote the first version of the btree bloat estimation query. part 1, In that case, it may just be better to take the outage to rebuild the primary key with the REINDEX command. GiST is built on B+ Tree indexes in a generalized format. definitely help the bloat estimation accuracy. This should be mapped and under control by autovacuum and/or your vacuum maintenance procedure. Below snippet displays output of table_bloat_check.sql query output. Now, it may turn out that some of these objects will have their bloat return to their previous values quickly again and those could be candidates for exclusion from the regular report. Here’s another example from another client that hadn’t really had any bloat monitoring in place at all before (that I was aware of anyway). This extra work is balanced by the reduced need … pgAudit. Table bloat is one of the most frequent reasons for bad performance, so it is important to either prevent it or make sure the table is allowed to shrink again. As always, there are caveats to this. However, the equivalent database table is 548MB. 9.5 introduced the SCHEMA level as well. seems to me there’s no solution for 7.4. A new query has been created to have a better bloat estimate for Btree indexes. The next option is to use the REINDEX command. If you’re running this on a UNIQUE index, you may run into an issue if it was created as a UNIQUE CONSTRAINT vs a UNIQUE INDEX. test3_i_md5_idx, here is the comparison of real bloat, estimation without September 25, 2017 Keith Fiske. So PostgreSQL gives you the option to use B+ trees where they come in handy. estimation for the biggest ones: the real index was smaller than the estimated If it is, you may want to re-evaluate how you’re using PostgreSQL (Ex. This small bug is not as bad for stats than previous ones, but fixing it “check_pgactivity” at some point. Functionally, they’re no different than a unique index with a NOT NULL constraint on the column. Also, if you’re running low on disk space, you may not have enough room for pg_repack since it requires rebuilding the entire table and all indexes in secondary tables before it can remove the original bloated table. For more informations about these queries, see … All writes are blocked to the table, but if a read-only query does not hit the index that you’re rebuilding, that is not blocked. have no opaque data, so no special space (good, I ‘ll not have to fix this bug I’ve just updated PgObserver also to use the latest from “check_pgactivity” (https://github.com/zalando/PGObserver/commit/ac3de84e71d6593f8e64f68a4b5eaad9ceb85803). The ASC and DESC specify the sort order. A handy command to get the definition of an index is pg_get_indexdef(regclass). As a demo, take a md5 string of 32 varlena types (text, bytea, etc) to the statistics(see The fundamental indexing system PostgreSQL uses is called a B-tree, which is a type of index that is optimized for storage systems. I was About me PostgreSQL contributor since 2015 • Index-only scan for GiST • Microvacuum for GiST • B-tree INCLUDE clause • B-tree. Taking the “text” type as example, PostgreSQL adds a one byte header to the I gave full command examples here so you can see the runtimes involved. These bugs have the same results: very bad estimation. Using the previous demo on Make sure to pick the correct one for your PostgreSQL version. So it has to do the extra work only occasionally, and only when it would have to do extra work anyway. I have read that the bloat can be around 5 times greater for tables than flat files so over 20 times seems quite excessive. A single metapage is stored in a fixed position at the start of the first segment file of the index. To be more precise PostgreSQL B-Tree implementation is based on Lehman & Yao Algorithm and B+-Trees. one! As I said above, I did use it where you see that initial huge drop in disk space on the first graph, but before that there was a rather large spike to get there. They’re the native methods built into the database and, as long as you don’t typo the DDL commands, not likely to be prone to any issues cropping up later down the road. For a delete a record is just flagged … bug took me back on this doc page Ordinary tables This means it is critically important to monitor your disk space usage if bloat turns out to be an issue for you. Over the next week or so I worked through roughly 80 bloated objects to recover about 270GB of disk space. things) to reference both siblings of the page in the tree. part 3. So it’s better to just make a unique index vs a constraint if possible. My post almost 2 years ago about checking for PostgreSQL bloat is still one of the most popular ones on my blog (according to Google Analytics anyway). If you’ve just got a plain old index (b-tree, gin or gist), there’s a combination of 3 commands that can clear up bloat with minimal downtime (depending on database activity). store whatever it needs for its own purpose. This is me first fixing one small, but very bloated index followed by running a pg_repack to take care of both table and a lot of index bloat. If you’re unable to use any of them, though, the pg_repack tool is very handy for removing table bloat or handling situations with very busy or complicated tables that cannot take extended outages. PostgreSQL wiki pages: Cheers, happy monitoring, happy REINDEX-ing! where I remembered I should probably pay attention to this space. But I figured I’d go through everything wasting more than a few hundred MB just so I can better assess what the actual normal bloat level of this database is. Compression of duplicates • pg_probackup firstname.lastname@example.org json is now the preferred, structured output method if you need to see more details outside of querying the stats table in the database. Checking for PostgreSQL Bloat. You have to drop & recreate a bloated index instead of rebuilding it concurrently, making previously fast queries extremely slow). “Opaque Data” in code sources. If anyone else has some handy tips for bloat cleanup, I’d definitely be interested in hearing them. The easiest, but most intrusive, bloat removal method is to just run a VACUUM FULL on the given table. Monitoring your bloat in Postgres Postgres under the covers in simplified terms is one giant append only log. md5, supposed to be 128 byte long: After removing this part of the query, stats for test3_i_md5_idx are much better: This is a nice bug fix AND one complexity out of the query. part 2 and One of these for the second client above took 4.5 hours to complete. For table bloat, Depesz wrote some blog posts a while ago that are still relevant with some interesting methods of moving data around on disk. For very small tables this is likely your best option. The bloat score on this table is a 7 since the dead tuples to active records ratio is 7:1. ignored in both cases, s the bloat sounds much bigger with the old version of I have read that the bloat can be around 5 times greater for tables than flat files so over 20 times seems quite excessive. PostgreSQL bloat. Index bloat is the most common occurrence, so I’ll start with that. Tagged with bloat, json, monitoring, postgresql, tuning, The Journalist template by Lucian E. Marin — Built for WordPress, Removing A Lot of Old Data (But Keeping Some Recent). Hi, I am using PostgreSQL 9.1 and loading very large tables ( 13 million rows each ). about them at some point. I should probably After deletions all pages would contain half of the records empty, i.e., bloat. This clears out 100% of the bloat in both the table and all indexes it contains at the expense of blocking all access for the duration. Neither the CREATE nor the DROP command will block any other sessions that happen to come in while this is running. The Index method Or type can be selected via the USING method. Now we can write our set of commands to rebuild the index. No dead tuples (so autovacuum is running efficiently) and 60% of the total index is free space that can be reclaimed. the headers was already added to them. Free 30 Day Trial. This is is a small space on each pages reserved to the access method so it can However, a pro… It's very easy to take for granted the statement CREATE INDEX ON some_table (some_column);as PostgreSQL does a lot of work to keep the index up-to-date as the values it stores are continuously inserted, updated, and deleted. Since it’s doing full scans on both tables and indexes, this has the potential to force data out of shared buffers. Giving the command to create a primary key an already existing unique index to use allows it to skip the creation and validation usually done with that command. But if you start getting more in there, that’s just taking a longer and longer outage for the foreign key validation which will lock all tables involved. Btree index, this “special space” is 16 bytes long and used (among other © 2010 - 2019: Jehan-Guillaume (ioguix) de Rorthais, current_database | schemaname | tblname | idxname | real_size | estimated_size | bloat_size | bloat_ratio | is_na, ------------------+------------+---------+-----------------+-----------+----------------+------------+----------------------------+-------, pagila | public | test | test_expression | 974848 | 335872 | 638976 | 65.5462184873949580 | f, current_database | schemaname | tblname | idxname | real_size | estimated_size | bloat_size | bloat_ratio | is_na, ------------------+------------+---------+-----------------+-----------+----------------+------------+------------------+-------, pagila | public | test | test_expression | 974848 | 851968 | 122880 | 12.6050420168067 | f, current_database | schemaname | tblname | idxname | real_size | estimated_size | bloat_size | bloat_ratio | is_na, ------------------+------------+---------+-----------------+-----------+----------------+------------+---------------------+-------, pagila | public | test3 | test3_i_md5_idx | 590536704 | 601776128 | -11239424 | -1.9032557881448805 | f, pagila | public | test3 | test3_i_md5_idx | 590536704 | 521535488 | 69001216 | 11.6844923495221052 | f, pagila | public | test3 | test3_i_md5_idx | 590536704 | 525139968 | 65396736 | 11.0741187731491 | f, https://gist.github.com/ioguix/dfa41eb0ef73e1cbd943, https://gist.github.com/ioguix/5f60e24a77828078ff5f, https://gist.github.com/ioguix/c29d5790b8b93bf81c27, https://wiki.postgresql.org/wiki/Index_Maintenance#New_query, https://wiki.postgresql.org/wiki/Show_database_bloat, https://github.com/zalando/PGObserver/commit/ac3de84e71d6593f8e64f68a4b5eaad9ceb85803. If the primary key, or any unique index for that matter, has any FOREIGN KEY references to it, you will not be able to drop that index without first dropping the foreign key(s).
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