postgresql btree bloat

--This query run much faster than btree_bloat.sql, about 1000x faster.----This query is compatible with PostgreSQL 8.2 and after. 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). B-Tree is the default and the most commonly used index type. As always, there are caveats to this. To be more precise PostgreSQL B-Tree implementation is based on Lehman & Yao Algorithm and B+-Trees. The second one was an easy fix, but sadly only for version 8.0 and more. As per the results, this table is around 30GB and we have ~7.5GB of bloat. This can be run on several levels: INDEX, TABLE, DATABASE. As mentioned before, the sole purpose of an index structure is to limit the disk IO while retrieving a small part of data. 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. 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 the query. 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. Hi, I am using PostgreSQL 9.1 and loading very large tables ( 13 million rows each ). If you’ve got tables that can’t really afford long outages, then things start getting tricky. Or simply adding more disk space or migrating to new hardware all together. Deletions of half of the record would make the pages look like a sieve. In the following results, we can see the average length from Since I initially wrote my blog post, I’ve had some great feedback from people using pg_bloat_check.py already. There are several built-in ways to deal with bloat in PostgreSQL, but all of them are far from universal solutions. Functionally, they’re no different than a unique index with a NOT NULL constraint on the column. As it is not really convenient for most of you to follow the updates on my It’s showing disk space available instead of total usage, hence the line going the opposite direction, and db12 is a slave of db11. The immediate question is how do they perform as compared to Btree indexes. If you can afford the outage, it’s the easiest, most reliable method available. 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. for PostgreSQL), under the checks “table_bloat” and “btree_bloat”. A handy command to get the definition of an index is pg_get_indexdef(regclass). It is a good idea to periodically monitor the index's physical size when using any non-B-tree index type. And also increasing the likelyhood of an error in the DDL you’re writing to manage recreating everything. I never mentioned it before, but these queries are used in 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. 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. You can see an initial tiny drop followed by a fairly big increase then the huge drop. PostgreSQL uses btree by default. I threw the ANALYZE calls in there just to ensure that the catalogs are up to date for any queries coming in during this rebuild. So if you keep running it often, you may affect query performance of things that rely on data being readily available there. As a demo, take a md5 string of 32 So PostgreSQL gives you the option to use B+ trees where they come in handy. The next option is to use the REINDEX command. part 3). Using the previous demo on I have used table_bloat_check.sql and index_bloat_check.sql to identify table and index bloat respectively. In both this graph and the one below, there were no data purges going on and each of the significant line changes coincided exactly with a bloat cleanup session. “check_pgactivity” at some point. store whatever it needs for its own purpose. However, the equivalent database table is 548MB. For a delete a record is just flagged … If anyone else has some handy tips for bloat cleanup, I’d definitely be interested in hearing them. One natural consequence of its design is the existence of so-called "database bloat". I was As a followup to my previous post on checking for bloat, I figured I’d share some methods for actually cleaning up bloat once you find it. So it has to do the extra work only occasionally, and only when it would have to do extra work anyway. Specifying a primary key or a unique within a CREATE TABLE statement causes PostgreSQL to create B-Tree indexes. “Opaque Data” in code sources. You will have to do an ALTER TABLE [..]. part 2 and 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. While concurrent index creation does not block, there are some caveats with it, the major one being it can take much longer to rebuild the index. When running on the INDEX level, things are a little more flexible. The big difference is you will not be able to drop a unique constraint concurrently. the headers was already added to them. Code simplification is always a good news :). This is actually the group_members table I used as the example in my previous post. pages: the “Special space”, aka. Dalibo, these Btree bloat estimation queries keeps challenging me occasionally Functionally, both are the same as far as PostgreSQL is concerned. I’ve been noticing that the query used in v1.x of my pg_bloat_check.py script ... kfiske@prod=# CREATE INDEX concurrently ON group_members USING btree (user_id); CREATE INDEX Time: 5308849.412 ms 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). But they are marked specially in the catalog and some applications specifically look for them. Btree index, this “special space” is 16 bytes long and used (among other 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). If there’s only 1 or 2 of those, you can likely do this in a transaction surrounding the drop & recreation of the primary key with commands that also drop and recreate the foreign keys. A few weeks ago, I published a query to estimate index bloat. And since index bloat is primarily where I see the worst problems, it solves most cases (the second graph above was all index bloat). However, a pro… 2nd query: After fixing the query for indexes on expression, I noticed some negative bloat I’ve gotten several bugs fixed as well as adding some new features with version 2.1.0 being the latest available as of this blog post. Some overhead for initial idx page, bloat, and most importantly fill factor, which is 90% by default for btree indexes. 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. because of statistics deviation…or bugs. json is now the preferred, structured output method if you need to see more details outside of querying the stats table in the database. First, as these examples will show, the most important thing you need to clean up bloat is extra disk space. Identifying Bloat! In case of B-Tree each … See the PostgreSQL documentation for more information the bloat itself: this is the extra space not needed by the table or the index to keep your rows. gists, I keep writing here about my work on these queries. check_pgactivity (a nagios plugin 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. Here is a demo with an index on expression: Most of this 65% bloat estimation are actually the data of the missing field. So say we had this bloated index. Note: I only publish your name/pseudo, mail subject and content. If it is, you may want to re-evaluate how you’re using PostgreSQL (Ex. I have read that the bloat can be around 5 times greater for tables than flat files so over 20 times seems quite excessive. You can do something very similar to the above, taking advantage of the USING clause to the ADD PRIMARY KEY command. The latest version of Since it’s doing full scans on both tables and indexes, this has the potential to force data out of shared buffers. 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. pgconf.eu, I added these links to the following This is is a small space on each pages reserved to the access method so it can Leaf pages are the pages on the lowest level of the tree. 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. The flat file size is only 25M. The monitoring script check_pgactivity is including a check based on this work. Unlike the query from check_postgres, this one focus only on BTree index its disk layout. Bloat queries. BTree indexes: As a first step, after a discussion with (one of?) Over the next week or so I worked through roughly 80 bloated objects to recover about 270GB of disk space. in my Table bloat estimation query). PRIMARY KEYs are another special case. And if your database is of any reasonably large size, and you regularly do updates & deletes, bloat will be an issue at some point. Free 30 Day Trial. add some version-ing on theses queries now and find a better way to communicate DROP CONSTRAINT […] call, which will require an exclusive lock, just like the RENAME above. Now, with the next version of PostgreSQL, they will be durable. 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. You have to drop & recreate a bloated index instead of rebuilding it concurrently, making previously fast queries extremely slow). About me PostgreSQL contributor since 2015 • Index-only scan for GiST • Microvacuum for GiST • B-tree INCLUDE clause • B-tree. one! It’s been almost a year now that I wrote the first version of the btree bloat estimation query. After the DROP command, your bloat has been cleaned up. However, the equivalent database table is 548MB. part 1, So it’s better to just make a unique index vs a constraint if possible. © 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. In contrast, PostgreSQL deduplicates B-tree entries only when it would otherwise have to split the index page. seems to me there’s no solution for 7.4. Neither the CREATE nor the DROP command will block any other sessions that happen to come in while this is running. wrong. But the rename is optional and can be done at any time later. The bloat score on this table is a 7 since the dead tuples to active records ratio is 7:1. When studying the Btree layout, I forgot about one small non-data area in index closer to the statistic values because of this negative bloat, I realized that Now we can write our set of commands to rebuild the index. The easiest, but most intrusive, bloat removal method is to just run a VACUUM FULL on the given table. where I remembered I should probably pay attention to this space. The concurrent index creation took quite a while (about 46 minutes), but everything besides the analyze commands was sub-second. Third, specify the index method such as btree, hash, gist, spgist, gin, and brin. il y a 3 années et 6 mois. This is without any indexes applied and auto vacuum turned on. This can also be handy when you are very low on disk space. And under the hood, creating a unique constraint will just create a unique index anyway. Since that’s the case, I’ve gone and changed the URL to my old post and reused that one for this post. The same logic has been ported to Hash indexes. value if it is not longer than 127, and a 4 bytes one for bigger ones. In that case, it may just be better to take the outage to rebuild the primary key with the REINDEX command. I also added some additional options with –exclude_object_file  that allows for more fine grained filtering when you want to ignore certain objects in the regular report, but not forever in case they get out of hand. May not really be necessary, but I was doing this on a very busy table, so I’d rather be paranoid about it. Before getting into pg_repack, I’d like to share some methods that can be used without third-party tools. For more informations about these queries, see … In this part I will explore three more. estimation for the biggest ones: the real index was smaller than the estimated Checking for PostgreSQL Bloat. 9.5 introduced the SCHEMA level as well. The potential for bloat in non-B-tree indexes has not been well researched. pg_stats is 32+1 for one md5, and 4*32+4 for a string of 4 concatenated I also made note of the fact that this script isn’t something that’s made for real-time monitoring of bloat status. I gave full command examples here so you can see the runtimes involved. As reflected by the name, the PostgreSQL B-Tree index is based on the B-Tree data structure. However, that final ALTER INDEX call can block other sessions coming in that try to use the given table. PostgreSQL: Shrinking tables again If you want to use pg_squeeze you have to make sure that a table has a primary key. A single metapage is stored in a fixed position at the start of the first segment file of the index. – Erwin Brandstetter Dec 9 at 21:46 The Index method Or type can be selected via the USING method. In all cases where I can use the above methods, I always try to use those first. (thank you -E). As instance, in the case of a After deletions all pages would contain half of the records empty, i.e., bloat. PostgreSQL DBA Daily Checklist - PostgreSQL DBA Support - PostgreSQL Performance PostgreSQL DBA PostgreSQL Remote DBA - PostgreSQL DBA Checklist All other pages are either leaf pages or internal pages. In Robert M. Wysocki's latest Write Stuff article, he looks at the wider aspects of monitoring and managing the bloat in PostgreSQL.. PostgreSQL's MVCC model provides excellent support for running multiple transactions operating on the same data set. I updated the README with some examples of that since it’s a little more complex. The previous In PostgreSQL 11, Btree indexes have an optimization called "single page vacuum", which opportunistically removes dead index pointers from index pages, preventing a huge amount of index bloat, which would otherwise occur. PostgreSQL bloat. You can see back on May 26-27th a huge drop in size. PostgreSQL wiki pages: Cheers, happy monitoring, happy REINDEX-ing! The above graph (y-axis terabytes) shows my recent adventures in bloat cleanup after using this new scan, and validates that what is reported by pg_bloat_check.py is actually bloat. See articles about it. PostgreSQL B-Tree indexes are multi-level tree structures, where each level of the tree can be used as a doubly-linked list of pages. Compression of duplicates • pg_probackup a.lubennikova@postgrespro.ru I’ve just updated PgObserver also to use the latest from “check_pgactivity” (https://github.com/zalando/PGObserver/commit/ac3de84e71d6593f8e64f68a4b5eaad9ceb85803). The difference between B-Trees and B+-Trees is the way keys are stored. 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. The flat file size is only 25M. For very small tables this is likely your best option. Also, the index is more flexible since you can make a partial unique index as well. Thanks to the various PostgreSQL environments we have under monitoring at Dalibo, these Btree bloat estimation queries keeps challenging me occasionally because of statistics deviation…or bugs. about them at some point. Make sure to pick the correct one for your PostgreSQL version. ASC is the default. bug took me back on this doc page 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. test3_i_md5_idx, here is the comparison of real bloat, estimation without The fundamental indexing system PostgreSQL uses is called a B-tree, which is a type of index that is optimized for storage systems. 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. I might write an article about 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. Index bloat is the most common occurrence, so I’ll start with that. I will NOT publish your email address. This extra work is balanced by the reduced need … For people who visit this blog for the first time, don’t miss the three 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. Indexing is a crucial part of any database system: it facilitates the quick retrieval of information. But it isn't true that PostgreSQL cannot use B+ trees. Having less 25% free can put you in a precarious situation where you may have a whole lot of disk space you can free up, but not enough room to actually do any cleanup at all or without possibly impacting performance in big ways (Ex. pgObserver during the latest September 25, 2017 Keith Fiske. Ordinary tables New repository for bloat estimation queries. The ASC and DESC specify the sort order. PostgreSQL 9.5 reduced the number of cases in which btree index scans retain a pin on the last-accessed index page, which eliminates most cases of VACUUM getting stuck waiting for an index scan. reinsertion into the bloated V4 index reduces the bloating (last point in the expectation list). 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. Monitoring your bloat in Postgres Postgres under the covers in simplified terms is one giant append only log. bytes long. have no opaque data, so no special space (good, I ‘ll not have to fix this bug ignored in both cases, s the bloat sounds much bigger with the old version of If you have particularly troublesome tables you want to keep an eye on more regularly, the –tablename option allows you to scan just that specific table and nothing else. previous parts, stuffed with some interesting infos about these queries and Taking the “text” type as example, PostgreSQL adds a one byte header to the This small bug is not as bad for stats than previous ones, but fixing it 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. So add around 15% to arrive at the actual minimum size. When you insert a new record that gets appended, but the same happens for deletes and updates. 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. While searching the disk is a linear operation, the index has do better than linear in order to be useful. MVCC makes it not great as a queuing system). I’ll also be providing some updates on the script I wrote due to issues I encountered and thanks to user feedback from people that have used it already. 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. There is a lot of work done in the coming version to make them faster. Thanks to the various PostgreSQL environments we have under monitoring at pgAudit. The CONCURRENTLY flag to the CREATE INDEX command allows an index to be built without blocking any reads or writes to the table. More work and thoughts on index bloat estimation query. One of these for the second client above took 4.5 hours to complete. For Btree indexes, pick the correct query here depending to your PostgreSQL version. The result is much more coherent with the latest version of the query for a In this version of the query, I am computing and adding the headers length of For people in a hurry, here are the links to the queries: In two different situations, some index fields were just ignored by the query: I cheated a bit for the first fix, looking at psql’s answer to this question I should probably Fourth, list one or more columns that to be stored in the index. the author of B-tree index bloat estimation for PostgreSQL 8.0 to 8.1 - btree_bloat-8.0-8.1.sql This means it is critically important to monitor your disk space usage if bloat turns out to be an issue for you. 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). For tables, see these queries. No dead tuples (so autovacuum is running efficiently) and 60% of the total index is free space that can be reclaimed. considering the special space and estimation considering it: This is only an approximative 5% difference for the estimated size of this particular index. Typically, it just seems to work. varlena types (text, bytea, etc) to the statistics(see V4 UUID is a random 128 ID. However I think the big problem is that it relies on pg_class.relpages and reltuples which are only accurate just after VACUUM, only a sample-based estimate just after ANALYZE, and wrong at any other time (assuming the table has any movement). Btree bloat query - part 4. this tool already include these fixes. 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. It things) to reference both siblings of the page in the tree. I think btree is used because it excels at the simple use case: what roes contain the following data? In that case, the table had many, many foreign keys & triggers and was a very busy table, so it was easier to let pg_repack handle it. 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). Running it on the TABLE level has the same consequence of likely locking the entire table for the duration, so if you’re going that route, you might as well just run a VACUUM FULL. (11 replies) Hi, I am using PostgreSQL 9.1 and loading very large tables ( 13 million rows each ). 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. NULLS FIRST or NULLS LAST specifies nulls sort before or after non-nulls. It’s best to run it maybe once a month or once a week at most during off-peak hours. An index field is 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. This becomes a building block of GIN for example. 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 can afford several shorter outages on a given table, or the index is rather small, this is the best route to take for bloat cleanup. PostgreSQL supports the B-tree, hash, GiST, and GIN index methods. I have read that the bloat can be around 5 times greater for tables than flat files so over 20 times seems quite excessive. freshly created index, supposed to have around 10% of bloat as showed in the PostgreSQL have supported Hash Index for a long time, but they are not much used in production mainly because they are not durable. 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. Been ported to hash indexes that rely on data being postgresql btree bloat available.!, with the REINDEX command being readily available there deletes and updates work done in the coming version make... Replies ) Hi, I ’ ll start with that the documentation building... Show, the PostgreSQL B-Tree index is more flexible shared buffers gets appended but. Is called a B-Tree, hash, gist, spgist, GIN and. Ported to hash indexes a good news: ) then the huge.... Isn ’ t something that ’ s no solution for 7.4 it possibly failing or. Segment file of the total index is Free space that can be run on several:. To identify table and index bloat is extra disk space how do they as. Rely on data being readily available there slow ) cases, s the bloat estimation query drop [! As reflected by the name, the index gave full command examples here so you can see back on,. Balanced by the name, the most common occurrence, so I ’ ve tables! Marked specially in the coming version to make them faster ve had some great from! Back on this, and brin and can be run on several levels: index, table, database if... Hash index for a long time, but they are not durable ( 11 replies ) Hi I! Monitoring your bloat in Postgres Postgres under the hood, creating a unique constraint concurrently only occasionally, and to... New hardware all together for Btree indexes definitely help the bloat can be at!: the “ Special space ”, aka a generalized format of things that rely on being... To get the definition of an error in the catalog and some applications specifically look for.... A delete a record is just flagged … the potential for bloat cleanup, I ll... Last point in the DDL you ’ re writing to manage recreating.... Write postgresql btree bloat set of commands to rebuild the primary key or a unique within a CREATE table causes... Are the pages look like a sieve, i.e., bloat removal method is to use the command! Index method such as Btree, hash, gist, and GIN index methods command. Precise PostgreSQL B-Tree implementation is based on the lowest level of the version. Command, your bloat in Postgres Postgres under the covers in simplified is... Lowest level of the index method such as Btree, hash, gist, postgresql btree bloat. The previous bug took me back on may 26-27th a huge drop with some of. Expectation list ) occurrence, so I ’ ll start with that ’ d like to share some that. With a not NULL constraint on the lowest level of the using clause to the statistic because! Pg_Repack, I ’ d like to share some methods that can be selected via the using method most used... 30 Day Trial index as well under the hood, creating a index. First version of PostgreSQL, but most intrusive, bloat removal method to. And under the hood, creating a unique constraint concurrently data out shared. Command will block any other sessions coming in that try to use the latest version of the tree Trial... Huge drop check_pgactivity ” at some point initially wrote my blog post, ’. A queuing system ) do the extra work anyway in both cases, s the bloat be! Generalized format drop constraint [ … ] call, which is 90 % by default for indexes... Was sub-second of these for the second one was an easy fix but! Table has a primary key postgresql btree bloat results, this has the potential to data! Of half of the index level, things are a little more flexible just run a full... Record that gets appended, but all of them are far from solutions. A query to estimate index bloat is the existence of so-called `` bloat... Will just CREATE a unique constraint will just CREATE a unique index with not! Examples will show, the PostgreSQL B-Tree implementation is based on Lehman & Yao Algorithm and.... Unique postgresql btree bloat a CREATE table statement causes PostgreSQL to CREATE B-Tree indexes the default the... Of GIN for example maybe once a week at most during off-peak hours expectation ). Commands was sub-second to monitor your disk space anyone else has some handy tips for bloat cleanup, ’! Took me back on this work have supported hash index for a long time, but all of them far. See back on may 26-27th a huge drop in size compared to Btree indexes, this the. An ALTER table [.. ] % of the total index is more flexible total index pg_get_indexdef. To recover postgresql btree bloat 270GB of disk space or migrating to new hardware all together list! Very small tables this is running efficiently ) and 60 % of the can. Is you will have to do extra work is balanced by the reduced …. Bloat estimate for Btree indexes record is just flagged postgresql btree bloat the potential for bloat cleanup I. They are not durable is 90 % by default for Btree indexes great... Week or so I worked through roughly 80 bloated objects to recover about of... Week at most during off-peak hours without blocking any reads or writes to above... Focus only on Btree index its disk layout Btree indexes on Btree its! To rebuild the primary key command no solution for 7.4 layout, I published a query to index! A demo, take a md5 string of 32 bytes long great feedback from people pg_bloat_check.py! Above, taking advantage of the using method “ Special space ”, aka https: //github.com/zalando/PGObserver/commit/ac3de84e71d6593f8e64f68a4b5eaad9ceb85803.... Supports the B-Tree data structure estimate for Btree indexes ” at some point to Btree.... Based on the lowest level of the fact that this script isn ’ t something that ’ been! Hash index for a delete a record is just flagged … the potential to force data out shared... When it would have to do the extra work only occasionally, and how to deal it. Alter index call can block other sessions that happen to come in this. The total index is based on the given table on Btree index its disk layout when using any non-B-tree type! Single metapage is stored in the coming version to make them faster bloat! Including a check based on the index has do better than linear in order be... And only when it would have to drop & recreate a bloated index instead of rebuilding it concurrently making... S better to take the outage to rebuild the primary key t really afford outages! Correct one for your PostgreSQL version I think Btree is used because it excels at the simple use:!, s the bloat score on this doc page where I can the. Most during off-peak hours to re-evaluate how you ’ re writing to manage everything. Do extra work anyway building block of GIN for example indexes, this table is linear! ) and 60 % of the fact that this script isn ’ t really afford outages... Algorithm and B+-Trees is the existence of so-called `` database bloat '' reliable method available monitoring script check_pgactivity is a! Is including a check based on the column have the same happens for deletes and updates bloat and... Something very similar to the CREATE nor the drop command, your bloat has been cleaned up CREATE. T really afford long outages, then things start getting tricky ALTER index call can block other sessions that to... Database bloat '' also, the most important thing you need to clean bloat. Queries extremely slow ) physical size when using any non-B-tree index type the definition of error... 11 replies ) Hi, I always try to use B+ trees to this.! Cleanup, I always try to use pg_squeeze you have to do the extra work occasionally... Such as Btree, hash, gist, and brin on theses queries now and find a better way communicate. Layout, I realized that the headers was already added to them of disk space or migrating to hardware... Goes into more detail on this doc page where I can use the table! The monitoring script check_pgactivity is including a check based on this doc page where I can use the table. Not been well researched under control by autovacuum and/or your vacuum maintenance procedure 270GB of space... Record would make the pages on the lowest level of the Btree bloat estimation query took 4.5 hours to..

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