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postgresql/src/include/access/brin.h

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BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
/*
* AM-callable functions for BRIN indexes
*
Update copyright for 2023 Backpatch-through: 11
2023-01-02 21:00:37 +01:00
* Portions Copyright (c) 1996-2023, PostgreSQL Global Development Group
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
* src/include/access/brin.h
*/
#ifndef BRIN_H
#define BRIN_H
#include "nodes/execnodes.h"
Allow parallel CREATE INDEX for BRIN indexes Allow using multiple worker processes to build BRIN index, which until now was supported only for BTREE indexes. For large tables this often results in significant speedup when the build is CPU-bound. The work is split in a simple way - each worker builds BRIN summaries on a subset of the table, determined by the regular parallel scan used to read the data, and feeds them into a shared tuplesort which sorts them by blkno (start of the range). The leader then reads this sorted stream of ranges, merges duplicates (which may happen if the parallel scan does not align with BRIN pages_per_range), and adds the resulting ranges into the index. The number of duplicate results produced by workers (requiring merging in the leader process) should be fairly small, thanks to how parallel scans assign chunks to workers. The likelihood of duplicate results may increase for higher pages_per_range values, but then there are fewer page ranges in total. In any case, we expect the merging to be much cheaper than summarization, so this should be a win. Most of the parallelism infrastructure is a simplified copy of the code used by BTREE indexes, omitting the parts irrelevant for BRIN indexes (e.g. uniqueness checks). This also introduces a new index AM flag amcanbuildparallel, determining whether to attempt to start parallel workers for the index build. Original patch by me, with reviews and substantial reworks by Matthias van de Meent, certainly enough to make him a co-author. Author: Tomas Vondra, Matthias van de Meent Reviewed-by: Matthias van de Meent Discussion: https://postgr.es/m/c2ee7d69-ce17-43f2-d1a0-9811edbda6e6%40enterprisedb.com
2023-12-08 18:15:23 +01:00
#include "storage/shm_toc.h"
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
#include "utils/relcache.h"
/*
* Storage type for BRIN's reloptions
*/
typedef struct BrinOptions
{
int32 vl_len_; /* varlena header (do not touch directly!) */
BlockNumber pagesPerRange;
BRIN auto-summarization Previously, only VACUUM would cause a page range to get initially summarized by BRIN indexes, which for some use cases takes too much time since the inserts occur. To avoid the delay, have brininsert request a summarization run for the previous range as soon as the first tuple is inserted into the first page of the next range. Autovacuum is in charge of processing these requests, after doing all the regular vacuuming/ analyzing work on tables. This doesn't impose any new tasks on autovacuum, because autovacuum was already in charge of doing summarizations. The only actual effect is to change the timing, i.e. that it occurs earlier. For this reason, we don't go any great lengths to record these requests very robustly; if they are lost because of a server crash or restart, they will happen at a later time anyway. Most of the new code here is in autovacuum, which can now be told about "work items" to process. This can be used for other things such as GIN pending list cleaning, perhaps visibility map bit setting, both of which are currently invoked during vacuum, but do not really depend on vacuum taking place. The requests are at the page range level, a granularity for which we did not have SQL-level access; we only had index-level summarization requests via brin_summarize_new_values(). It seems reasonable to add SQL-level access to range-level summarization too, so add a function brin_summarize_range() to do that. Authors: Álvaro Herrera, based on sketch from Simon Riggs. Reviewed-by: Thomas Munro. Discussion: https://postgr.es/m/20170301045823.vneqdqkmsd4as4ds@alvherre.pgsql
2017-04-01 19:00:53 +02:00
bool autosummarize;
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
} BrinOptions;
Fix BRIN cost estimation The original code was overly optimistic about the cost of scanning a BRIN index, leading to BRIN indexes being selected when they'd be a worse choice than some other index. This complete rewrite should be more accurate. Author: David Rowley, based on an earlier patch by Emre Hasegeli Reviewed-by: Emre Hasegeli Discussion: https://postgr.es/m/CAKJS1f9n-Wapop5Xz1dtGdpdqmzeGqQK4sV2MK-zZugfC14Xtw@mail.gmail.com
2017-04-06 22:49:26 +02:00
/*
* BrinStatsData represents stats data for planner use
*/
typedef struct BrinStatsData
{
BlockNumber pagesPerRange;
BlockNumber revmapNumPages;
} BrinStatsData;
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
#define BRIN_DEFAULT_PAGES_PER_RANGE 128
#define BrinGetPagesPerRange(relation) \
Refactor reloption handling for index AMs in-core This reworks the reloption parsing and build of a couple of index AMs by creating new structures for each index AM's options. This split was already done for BRIN, GIN and GiST (which actually has a fillfactor parameter), but not for hash, B-tree and SPGiST which relied on StdRdOptions due to an overlap with the default option set. This saves a couple of bytes for rd_options in each relcache entry with indexes making use of relation options, and brings more consistency between all index AMs. While on it, add a couple of AssertMacro() calls to make sure that utility macros to grab values of reloptions are used with the expected index AM. Author: Nikolay Shaplov Reviewed-by: Amit Langote, Michael Paquier, Álvaro Herrera, Dent John Discussion: https://postgr.es/m/4127670.gFlpRb6XCm@x200m
2019-11-25 01:40:53 +01:00
(AssertMacro(relation->rd_rel->relkind == RELKIND_INDEX && \
relation->rd_rel->relam == BRIN_AM_OID), \
(relation)->rd_options ? \
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
((BrinOptions *) (relation)->rd_options)->pagesPerRange : \
BRIN_DEFAULT_PAGES_PER_RANGE)
BRIN auto-summarization Previously, only VACUUM would cause a page range to get initially summarized by BRIN indexes, which for some use cases takes too much time since the inserts occur. To avoid the delay, have brininsert request a summarization run for the previous range as soon as the first tuple is inserted into the first page of the next range. Autovacuum is in charge of processing these requests, after doing all the regular vacuuming/ analyzing work on tables. This doesn't impose any new tasks on autovacuum, because autovacuum was already in charge of doing summarizations. The only actual effect is to change the timing, i.e. that it occurs earlier. For this reason, we don't go any great lengths to record these requests very robustly; if they are lost because of a server crash or restart, they will happen at a later time anyway. Most of the new code here is in autovacuum, which can now be told about "work items" to process. This can be used for other things such as GIN pending list cleaning, perhaps visibility map bit setting, both of which are currently invoked during vacuum, but do not really depend on vacuum taking place. The requests are at the page range level, a granularity for which we did not have SQL-level access; we only had index-level summarization requests via brin_summarize_new_values(). It seems reasonable to add SQL-level access to range-level summarization too, so add a function brin_summarize_range() to do that. Authors: Álvaro Herrera, based on sketch from Simon Riggs. Reviewed-by: Thomas Munro. Discussion: https://postgr.es/m/20170301045823.vneqdqkmsd4as4ds@alvherre.pgsql
2017-04-01 19:00:53 +02:00
#define BrinGetAutoSummarize(relation) \
Refactor reloption handling for index AMs in-core This reworks the reloption parsing and build of a couple of index AMs by creating new structures for each index AM's options. This split was already done for BRIN, GIN and GiST (which actually has a fillfactor parameter), but not for hash, B-tree and SPGiST which relied on StdRdOptions due to an overlap with the default option set. This saves a couple of bytes for rd_options in each relcache entry with indexes making use of relation options, and brings more consistency between all index AMs. While on it, add a couple of AssertMacro() calls to make sure that utility macros to grab values of reloptions are used with the expected index AM. Author: Nikolay Shaplov Reviewed-by: Amit Langote, Michael Paquier, Álvaro Herrera, Dent John Discussion: https://postgr.es/m/4127670.gFlpRb6XCm@x200m
2019-11-25 01:40:53 +01:00
(AssertMacro(relation->rd_rel->relkind == RELKIND_INDEX && \
relation->rd_rel->relam == BRIN_AM_OID), \
(relation)->rd_options ? \
BRIN auto-summarization Previously, only VACUUM would cause a page range to get initially summarized by BRIN indexes, which for some use cases takes too much time since the inserts occur. To avoid the delay, have brininsert request a summarization run for the previous range as soon as the first tuple is inserted into the first page of the next range. Autovacuum is in charge of processing these requests, after doing all the regular vacuuming/ analyzing work on tables. This doesn't impose any new tasks on autovacuum, because autovacuum was already in charge of doing summarizations. The only actual effect is to change the timing, i.e. that it occurs earlier. For this reason, we don't go any great lengths to record these requests very robustly; if they are lost because of a server crash or restart, they will happen at a later time anyway. Most of the new code here is in autovacuum, which can now be told about "work items" to process. This can be used for other things such as GIN pending list cleaning, perhaps visibility map bit setting, both of which are currently invoked during vacuum, but do not really depend on vacuum taking place. The requests are at the page range level, a granularity for which we did not have SQL-level access; we only had index-level summarization requests via brin_summarize_new_values(). It seems reasonable to add SQL-level access to range-level summarization too, so add a function brin_summarize_range() to do that. Authors: Álvaro Herrera, based on sketch from Simon Riggs. Reviewed-by: Thomas Munro. Discussion: https://postgr.es/m/20170301045823.vneqdqkmsd4as4ds@alvherre.pgsql
2017-04-01 19:00:53 +02:00
((BrinOptions *) (relation)->rd_options)->autosummarize : \
false)
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
Fix BRIN cost estimation The original code was overly optimistic about the cost of scanning a BRIN index, leading to BRIN indexes being selected when they'd be a worse choice than some other index. This complete rewrite should be more accurate. Author: David Rowley, based on an earlier patch by Emre Hasegeli Reviewed-by: Emre Hasegeli Discussion: https://postgr.es/m/CAKJS1f9n-Wapop5Xz1dtGdpdqmzeGqQK4sV2MK-zZugfC14Xtw@mail.gmail.com
2017-04-06 22:49:26 +02:00
extern void brinGetStats(Relation index, BrinStatsData *stats);
Allow parallel CREATE INDEX for BRIN indexes Allow using multiple worker processes to build BRIN index, which until now was supported only for BTREE indexes. For large tables this often results in significant speedup when the build is CPU-bound. The work is split in a simple way - each worker builds BRIN summaries on a subset of the table, determined by the regular parallel scan used to read the data, and feeds them into a shared tuplesort which sorts them by blkno (start of the range). The leader then reads this sorted stream of ranges, merges duplicates (which may happen if the parallel scan does not align with BRIN pages_per_range), and adds the resulting ranges into the index. The number of duplicate results produced by workers (requiring merging in the leader process) should be fairly small, thanks to how parallel scans assign chunks to workers. The likelihood of duplicate results may increase for higher pages_per_range values, but then there are fewer page ranges in total. In any case, we expect the merging to be much cheaper than summarization, so this should be a win. Most of the parallelism infrastructure is a simplified copy of the code used by BTREE indexes, omitting the parts irrelevant for BRIN indexes (e.g. uniqueness checks). This also introduces a new index AM flag amcanbuildparallel, determining whether to attempt to start parallel workers for the index build. Original patch by me, with reviews and substantial reworks by Matthias van de Meent, certainly enough to make him a co-author. Author: Tomas Vondra, Matthias van de Meent Reviewed-by: Matthias van de Meent Discussion: https://postgr.es/m/c2ee7d69-ce17-43f2-d1a0-9811edbda6e6%40enterprisedb.com
2023-12-08 18:15:23 +01:00
extern void _brin_parallel_build_main(dsm_segment *seg, shm_toc *toc);
BRIN: Block Range Indexes BRIN is a new index access method intended to accelerate scans of very large tables, without the maintenance overhead of btrees or other traditional indexes. They work by maintaining "summary" data about block ranges. Bitmap index scans work by reading each summary tuple and comparing them with the query quals; all pages in the range are returned in a lossy TID bitmap if the quals are consistent with the values in the summary tuple, otherwise not. Normal index scans are not supported because these indexes do not store TIDs. As new tuples are added into the index, the summary information is updated (if the block range in which the tuple is added is already summarized) or not; in the latter case, a subsequent pass of VACUUM or the brin_summarize_new_values() function will create the summary information. For data types with natural 1-D sort orders, the summary info consists of the maximum and the minimum values of each indexed column within each page range. This type of operator class we call "Minmax", and we supply a bunch of them for most data types with B-tree opclasses. Since the BRIN code is generalized, other approaches are possible for things such as arrays, geometric types, ranges, etc; even for things such as enum types we could do something different than minmax with better results. In this commit I only include minmax. Catalog version bumped due to new builtin catalog entries. There's more that could be done here, but this is a good step forwards. Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera, with contribution by Heikki Linnakangas. Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas. Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo. PS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 318633.
2014-11-07 20:38:14 +01:00
#endif /* BRIN_H */