postgresql/src/include/catalog/pg_amproc.h

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/*-------------------------------------------------------------------------
*
* pg_amproc.h
* definition of the system "amproc" relation (pg_amproc)
* along with the relation's initial contents.
*
* The amproc table identifies support procedures associated with index
* operator families and classes. These procedures can't be listed in pg_amop
* since they are not the implementation of any indexable operator.
*
* The primary key for this table is <amprocfamily, amproclefttype,
* amprocrighttype, amprocnum>. The "default" support functions for a
* particular opclass within the family are those with amproclefttype =
* amprocrighttype = opclass's opcintype. These are the ones loaded into the
* relcache for an index and typically used for internal index operations.
* Other support functions are typically used to handle cross-type indexable
* operators with oprleft/oprright matching the entry's amproclefttype and
* amprocrighttype. The exact behavior depends on the index AM, however, and
* some don't pay attention to non-default functions at all.
*
*
2017-01-03 19:48:53 +01:00
* Portions Copyright (c) 1996-2017, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
2010-09-20 22:08:53 +02:00
* src/include/catalog/pg_amproc.h
*
* NOTES
* the genbki.pl script reads this file and generates .bki
* information from the DATA() statements.
*
*-------------------------------------------------------------------------
*/
#ifndef PG_AMPROC_H
#define PG_AMPROC_H
#include "catalog/genbki.h"
/* ----------------
* pg_amproc definition. cpp turns this into
* typedef struct FormData_pg_amproc
* ----------------
*/
#define AccessMethodProcedureRelationId 2603
CATALOG(pg_amproc,2603)
{
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Oid amprocfamily; /* the index opfamily this entry is for */
Oid amproclefttype; /* procedure's left input data type */
Oid amprocrighttype; /* procedure's right input data type */
int16 amprocnum; /* support procedure index */
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regproc amproc; /* OID of the proc */
} FormData_pg_amproc;
/* ----------------
* Form_pg_amproc corresponds to a pointer to a tuple with
* the format of pg_amproc relation.
* ----------------
*/
typedef FormData_pg_amproc *Form_pg_amproc;
/* ----------------
* compiler constants for pg_amproc
* ----------------
*/
#define Natts_pg_amproc 5
#define Anum_pg_amproc_amprocfamily 1
#define Anum_pg_amproc_amproclefttype 2
#define Anum_pg_amproc_amprocrighttype 3
#define Anum_pg_amproc_amprocnum 4
#define Anum_pg_amproc_amproc 5
/* ----------------
* initial contents of pg_amproc
* ----------------
*/
/* btree */
DATA(insert ( 397 2277 2277 1 382 ));
DATA(insert ( 421 702 702 1 357 ));
DATA(insert ( 423 1560 1560 1 1596 ));
DATA(insert ( 424 16 16 1 1693 ));
DATA(insert ( 426 1042 1042 1 1078 ));
DATA(insert ( 426 1042 1042 2 3328 ));
DATA(insert ( 428 17 17 1 1954 ));
DATA(insert ( 428 17 17 2 3331 ));
DATA(insert ( 429 18 18 1 358 ));
DATA(insert ( 434 1082 1082 1 1092 ));
DATA(insert ( 434 1082 1082 2 3136 ));
DATA(insert ( 434 1082 1114 1 2344 ));
DATA(insert ( 434 1082 1184 1 2357 ));
DATA(insert ( 434 1114 1114 1 2045 ));
DATA(insert ( 434 1114 1114 2 3137 ));
DATA(insert ( 434 1114 1082 1 2370 ));
DATA(insert ( 434 1114 1184 1 2526 ));
DATA(insert ( 434 1184 1184 1 1314 ));
DATA(insert ( 434 1184 1184 2 3137 ));
DATA(insert ( 434 1184 1082 1 2383 ));
DATA(insert ( 434 1184 1114 1 2533 ));
DATA(insert ( 1970 700 700 1 354 ));
DATA(insert ( 1970 700 700 2 3132 ));
DATA(insert ( 1970 700 701 1 2194 ));
DATA(insert ( 1970 701 701 1 355 ));
DATA(insert ( 1970 701 701 2 3133 ));
DATA(insert ( 1970 701 700 1 2195 ));
DATA(insert ( 1974 869 869 1 926 ));
DATA(insert ( 1976 21 21 1 350 ));
DATA(insert ( 1976 21 21 2 3129 ));
DATA(insert ( 1976 21 23 1 2190 ));
DATA(insert ( 1976 21 20 1 2192 ));
DATA(insert ( 1976 23 23 1 351 ));
DATA(insert ( 1976 23 23 2 3130 ));
DATA(insert ( 1976 23 20 1 2188 ));
DATA(insert ( 1976 23 21 1 2191 ));
DATA(insert ( 1976 20 20 1 842 ));
DATA(insert ( 1976 20 20 2 3131 ));
DATA(insert ( 1976 20 23 1 2189 ));
DATA(insert ( 1976 20 21 1 2193 ));
DATA(insert ( 1982 1186 1186 1 1315 ));
DATA(insert ( 1984 829 829 1 836 ));
DATA(insert ( 1984 829 829 2 3359 ));
DATA(insert ( 1986 19 19 1 359 ));
DATA(insert ( 1986 19 19 2 3135 ));
DATA(insert ( 1988 1700 1700 1 1769 ));
DATA(insert ( 1988 1700 1700 2 3283 ));
DATA(insert ( 1989 26 26 1 356 ));
DATA(insert ( 1989 26 26 2 3134 ));
DATA(insert ( 1991 30 30 1 404 ));
DATA(insert ( 1994 25 25 1 360 ));
DATA(insert ( 1994 25 25 2 3255 ));
DATA(insert ( 1996 1083 1083 1 1107 ));
DATA(insert ( 2000 1266 1266 1 1358 ));
DATA(insert ( 2002 1562 1562 1 1672 ));
DATA(insert ( 2095 25 25 1 2166 ));
DATA(insert ( 2095 25 25 2 3332 ));
DATA(insert ( 2097 1042 1042 1 2180 ));
DATA(insert ( 2097 1042 1042 2 3333 ));
DATA(insert ( 2099 790 790 1 377 ));
DATA(insert ( 2233 703 703 1 380 ));
DATA(insert ( 2234 704 704 1 381 ));
DATA(insert ( 2789 27 27 1 2794 ));
DATA(insert ( 2968 2950 2950 1 2960 ));
DATA(insert ( 2968 2950 2950 2 3300 ));
DATA(insert ( 2994 2249 2249 1 2987 ));
DATA(insert ( 3194 2249 2249 1 3187 ));
DATA(insert ( 3253 3220 3220 1 3251 ));
DATA(insert ( 3371 774 774 1 4119 ));
DATA(insert ( 3522 3500 3500 1 3514 ));
DATA(insert ( 3626 3614 3614 1 3622 ));
DATA(insert ( 3683 3615 3615 1 3668 ));
DATA(insert ( 3901 3831 3831 1 3870 ));
DATA(insert ( 4033 3802 3802 1 4044 ));
/* hash */
DATA(insert ( 427 1042 1042 1 1080 ));
DATA(insert ( 431 18 18 1 454 ));
DATA(insert ( 435 1082 1082 1 450 ));
DATA(insert ( 627 2277 2277 1 626 ));
DATA(insert ( 1971 700 700 1 451 ));
DATA(insert ( 1971 701 701 1 452 ));
DATA(insert ( 1975 869 869 1 422 ));
DATA(insert ( 1977 21 21 1 449 ));
DATA(insert ( 1977 23 23 1 450 ));
DATA(insert ( 1977 20 20 1 949 ));
DATA(insert ( 1983 1186 1186 1 1697 ));
DATA(insert ( 1985 829 829 1 399 ));
DATA(insert ( 1987 19 19 1 455 ));
DATA(insert ( 1990 26 26 1 453 ));
DATA(insert ( 1992 30 30 1 457 ));
DATA(insert ( 1995 25 25 1 400 ));
DATA(insert ( 1997 1083 1083 1 1688 ));
DATA(insert ( 1998 1700 1700 1 432 ));
DATA(insert ( 1999 1184 1184 1 2039 ));
DATA(insert ( 2001 1266 1266 1 1696 ));
DATA(insert ( 2040 1114 1114 1 2039 ));
DATA(insert ( 2222 16 16 1 454 ));
DATA(insert ( 2223 17 17 1 456 ));
DATA(insert ( 2225 28 28 1 450 ));
DATA(insert ( 2226 29 29 1 450 ));
DATA(insert ( 2227 702 702 1 450 ));
DATA(insert ( 2228 703 703 1 450 ));
DATA(insert ( 2229 25 25 1 400 ));
DATA(insert ( 2231 1042 1042 1 1080 ));
DATA(insert ( 2235 1033 1033 1 329 ));
DATA(insert ( 2969 2950 2950 1 2963 ));
DATA(insert ( 3254 3220 3220 1 3252 ));
DATA(insert ( 3372 774 774 1 328 ));
DATA(insert ( 3523 3500 3500 1 3515 ));
DATA(insert ( 3903 3831 3831 1 3902 ));
DATA(insert ( 4034 3802 3802 1 4045 ));
/* gist */
DATA(insert ( 1029 600 600 1 2179 ));
DATA(insert ( 1029 600 600 2 2583 ));
DATA(insert ( 1029 600 600 3 1030 ));
DATA(insert ( 1029 600 600 4 2580 ));
DATA(insert ( 1029 600 600 5 2581 ));
DATA(insert ( 1029 600 600 6 2582 ));
DATA(insert ( 1029 600 600 7 2584 ));
DATA(insert ( 1029 600 600 8 3064 ));
DATA(insert ( 1029 600 600 9 3282 ));
DATA(insert ( 2593 603 603 1 2578 ));
DATA(insert ( 2593 603 603 2 2583 ));
DATA(insert ( 2593 603 603 3 2579 ));
DATA(insert ( 2593 603 603 4 2580 ));
DATA(insert ( 2593 603 603 5 2581 ));
DATA(insert ( 2593 603 603 6 2582 ));
DATA(insert ( 2593 603 603 7 2584 ));
DATA(insert ( 2593 603 603 9 3281 ));
DATA(insert ( 2594 604 604 1 2585 ));
DATA(insert ( 2594 604 604 2 2583 ));
DATA(insert ( 2594 604 604 3 2586 ));
DATA(insert ( 2594 604 604 4 2580 ));
DATA(insert ( 2594 604 604 5 2581 ));
DATA(insert ( 2594 604 604 6 2582 ));
DATA(insert ( 2594 604 604 7 2584 ));
DATA(insert ( 2594 604 604 8 3288 ));
DATA(insert ( 2595 718 718 1 2591 ));
DATA(insert ( 2595 718 718 2 2583 ));
DATA(insert ( 2595 718 718 3 2592 ));
DATA(insert ( 2595 718 718 4 2580 ));
DATA(insert ( 2595 718 718 5 2581 ));
DATA(insert ( 2595 718 718 6 2582 ));
DATA(insert ( 2595 718 718 7 2584 ));
Fix assorted inconsistencies in GiST opclass support function declarations. The conventions specified by the GiST SGML documentation were widely ignored. For example, the strategy-number argument for "consistent" and "distance" functions is specified to be a smallint, but most of the built-in support functions declared it as an integer, and for that matter the core code passed it using Int32GetDatum not Int16GetDatum. None of that makes any real difference at runtime, but it's quite confusing for newcomers to the code, and it makes it very hard to write an amvalidate() function that checks support function signatures. So let's try to instill some consistency here. Another similar issue is that the "query" argument is not of a single well-defined type, but could have different types depending on the strategy (corresponding to search operators with different righthand-side argument types). Some of the functions threw up their hands and declared the query argument as being of "internal" type, which surely isn't right ("any" would have been more appropriate); but the majority position seemed to be to declare it as being of the indexed data type, corresponding to a search operator with both input types the same. So I've specified a convention that that's what to do always. Also, the result of the "union" support function actually must be of the index's storage type, but the documentation suggested declaring it to return "internal", and some of the functions followed that. Standardize on telling the truth, instead. Similarly, standardize on declaring the "same" function's inputs as being of the storage type, not "internal". Also, somebody had forgotten to add the "recheck" argument to both the documentation of the "distance" support function and all of their SQL declarations, even though the C code was happily using that argument. Clean that up too. Fix up some other omissions in the docs too, such as documenting that union's second input argument is vestigial. So far as the errors in core function declarations go, we can just fix pg_proc.h and bump catversion. Adjusting the erroneous declarations in contrib modules is more debatable: in principle any change in those scripts should involve an extension version bump, which is a pain. However, since these changes are purely cosmetic and make no functional difference, I think we can get away without doing that.
2016-01-19 18:04:32 +01:00
DATA(insert ( 2595 718 718 8 3280 ));
DATA(insert ( 3655 3614 3614 1 3654 ));
DATA(insert ( 3655 3614 3614 2 3651 ));
DATA(insert ( 3655 3614 3614 3 3648 ));
DATA(insert ( 3655 3614 3614 4 3649 ));
DATA(insert ( 3655 3614 3614 5 3653 ));
DATA(insert ( 3655 3614 3614 6 3650 ));
DATA(insert ( 3655 3614 3614 7 3652 ));
DATA(insert ( 3702 3615 3615 1 3701 ));
DATA(insert ( 3702 3615 3615 2 3698 ));
DATA(insert ( 3702 3615 3615 3 3695 ));
DATA(insert ( 3702 3615 3615 4 3696 ));
DATA(insert ( 3702 3615 3615 5 3700 ));
DATA(insert ( 3702 3615 3615 6 3697 ));
DATA(insert ( 3702 3615 3615 7 3699 ));
DATA(insert ( 3919 3831 3831 1 3875 ));
DATA(insert ( 3919 3831 3831 2 3876 ));
DATA(insert ( 3919 3831 3831 3 3877 ));
DATA(insert ( 3919 3831 3831 4 3878 ));
DATA(insert ( 3919 3831 3831 5 3879 ));
DATA(insert ( 3919 3831 3831 6 3880 ));
DATA(insert ( 3919 3831 3831 7 3881 ));
DATA(insert ( 3919 3831 3831 9 3996 ));
DATA(insert ( 3550 869 869 1 3553 ));
DATA(insert ( 3550 869 869 2 3554 ));
DATA(insert ( 3550 869 869 3 3555 ));
DATA(insert ( 3550 869 869 4 3556 ));
DATA(insert ( 3550 869 869 5 3557 ));
DATA(insert ( 3550 869 869 6 3558 ));
DATA(insert ( 3550 869 869 7 3559 ));
DATA(insert ( 3550 869 869 9 3573 ));
/* gin */
Replace the built-in GIN array opclasses with a single polymorphic opclass. We had thirty different GIN array opclasses sharing the same operators and support functions. That still didn't cover all the built-in types, nor did it cover arrays of extension-added types. What we want is a single polymorphic opclass for "anyarray". There were two missing features needed to make this possible: 1. We have to be able to declare the index storage type as ANYELEMENT when the opclass is declared to index ANYARRAY. This just takes a few more lines in index_create(). Although this currently seems of use only for GIN, there's no reason to make index_create() restrict it to that. 2. We have to be able to identify the proper GIN compare function for the index storage type. This patch proceeds by making the compare function optional in GIN opclass definitions, and specifying that the default btree comparison function for the index storage type will be looked up when the opclass omits it. Again, that seems pretty generically useful. Since the comparison function lookup is done in initGinState(), making use of the second feature adds an additional cache lookup to GIN index access setup. It seems unlikely that that would be very noticeable given the other costs involved, but maybe at some point we should consider making GinState data persist longer than it now does --- we could keep it in the index relcache entry, perhaps. Rather fortuitously, we don't seem to need to do anything to get this change to play nice with dump/reload or pg_upgrade scenarios: the new opclass definition is automatically selected to replace existing index definitions, and the on-disk data remains compatible. Also, if a user has created a custom opclass definition for a non-builtin type, this doesn't break that, since CREATE INDEX will prefer an exact match to opcintype over a match to ANYARRAY. However, if there's anyone out there with handwritten DDL that explicitly specifies _bool_ops or one of the other replaced opclass names, they'll need to adjust that. Tom Lane, reviewed by Enrique Meneses Discussion: <14436.1470940379@sss.pgh.pa.us>
2016-09-26 20:52:44 +02:00
DATA(insert ( 2745 2277 2277 2 2743 ));
DATA(insert ( 2745 2277 2277 3 2774 ));
DATA(insert ( 2745 2277 2277 4 2744 ));
DATA(insert ( 2745 2277 2277 6 3920 ));
DATA(insert ( 3659 3614 3614 1 3724 ));
DATA(insert ( 3659 3614 3614 2 3656 ));
DATA(insert ( 3659 3614 3614 3 3657 ));
DATA(insert ( 3659 3614 3614 4 3658 ));
DATA(insert ( 3659 3614 3614 5 2700 ));
DATA(insert ( 3659 3614 3614 6 3921 ));
DATA(insert ( 4036 3802 3802 1 3480 ));
DATA(insert ( 4036 3802 3802 2 3482 ));
DATA(insert ( 4036 3802 3802 3 3483 ));
DATA(insert ( 4036 3802 3802 4 3484 ));
DATA(insert ( 4036 3802 3802 6 3488 ));
DATA(insert ( 4037 3802 3802 1 351 ));
DATA(insert ( 4037 3802 3802 2 3485 ));
DATA(insert ( 4037 3802 3802 3 3486 ));
DATA(insert ( 4037 3802 3802 4 3487 ));
DATA(insert ( 4037 3802 3802 6 3489 ));
/* sp-gist */
DATA(insert ( 3474 3831 3831 1 3469 ));
DATA(insert ( 3474 3831 3831 2 3470 ));
DATA(insert ( 3474 3831 3831 3 3471 ));
DATA(insert ( 3474 3831 3831 4 3472 ));
DATA(insert ( 3474 3831 3831 5 3473 ));
DATA(insert ( 3794 869 869 1 3795 ));
DATA(insert ( 3794 869 869 2 3796 ));
DATA(insert ( 3794 869 869 3 3797 ));
DATA(insert ( 3794 869 869 4 3798 ));
DATA(insert ( 3794 869 869 5 3799 ));
DATA(insert ( 4015 600 600 1 4018 ));
DATA(insert ( 4015 600 600 2 4019 ));
DATA(insert ( 4015 600 600 3 4020 ));
DATA(insert ( 4015 600 600 4 4021 ));
DATA(insert ( 4015 600 600 5 4022 ));
DATA(insert ( 4016 600 600 1 4023 ));
DATA(insert ( 4016 600 600 2 4024 ));
DATA(insert ( 4016 600 600 3 4025 ));
DATA(insert ( 4016 600 600 4 4026 ));
DATA(insert ( 4016 600 600 5 4022 ));
DATA(insert ( 4017 25 25 1 4027 ));
DATA(insert ( 4017 25 25 2 4028 ));
DATA(insert ( 4017 25 25 3 4029 ));
DATA(insert ( 4017 25 25 4 4030 ));
DATA(insert ( 4017 25 25 5 4031 ));
DATA(insert ( 5000 603 603 1 5012 ));
DATA(insert ( 5000 603 603 2 5013 ));
DATA(insert ( 5000 603 603 3 5014 ));
DATA(insert ( 5000 603 603 4 5015 ));
DATA(insert ( 5000 603 603 5 5016 ));
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
/* BRIN opclasses */
/* minmax bytea */
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DATA(insert ( 4064 17 17 1 3383 ));
DATA(insert ( 4064 17 17 2 3384 ));
DATA(insert ( 4064 17 17 3 3385 ));
DATA(insert ( 4064 17 17 4 3386 ));
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
/* minmax "char" */
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DATA(insert ( 4062 18 18 1 3383 ));
DATA(insert ( 4062 18 18 2 3384 ));
DATA(insert ( 4062 18 18 3 3385 ));
DATA(insert ( 4062 18 18 4 3386 ));
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
/* minmax name */
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DATA(insert ( 4065 19 19 1 3383 ));
DATA(insert ( 4065 19 19 2 3384 ));
DATA(insert ( 4065 19 19 3 3385 ));
DATA(insert ( 4065 19 19 4 3386 ));
/* minmax integer: int2, int4, int8 */
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DATA(insert ( 4054 20 20 1 3383 ));
DATA(insert ( 4054 20 20 2 3384 ));
DATA(insert ( 4054 20 20 3 3385 ));
DATA(insert ( 4054 20 20 4 3386 ));
DATA(insert ( 4054 20 21 1 3383 ));
DATA(insert ( 4054 20 21 2 3384 ));
DATA(insert ( 4054 20 21 3 3385 ));
DATA(insert ( 4054 20 21 4 3386 ));
DATA(insert ( 4054 20 23 1 3383 ));
DATA(insert ( 4054 20 23 2 3384 ));
DATA(insert ( 4054 20 23 3 3385 ));
DATA(insert ( 4054 20 23 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4054 21 21 1 3383 ));
DATA(insert ( 4054 21 21 2 3384 ));
DATA(insert ( 4054 21 21 3 3385 ));
DATA(insert ( 4054 21 21 4 3386 ));
DATA(insert ( 4054 21 20 1 3383 ));
DATA(insert ( 4054 21 20 2 3384 ));
DATA(insert ( 4054 21 20 3 3385 ));
DATA(insert ( 4054 21 20 4 3386 ));
DATA(insert ( 4054 21 23 1 3383 ));
DATA(insert ( 4054 21 23 2 3384 ));
DATA(insert ( 4054 21 23 3 3385 ));
DATA(insert ( 4054 21 23 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4054 23 23 1 3383 ));
DATA(insert ( 4054 23 23 2 3384 ));
DATA(insert ( 4054 23 23 3 3385 ));
DATA(insert ( 4054 23 23 4 3386 ));
DATA(insert ( 4054 23 20 1 3383 ));
DATA(insert ( 4054 23 20 2 3384 ));
DATA(insert ( 4054 23 20 3 3385 ));
DATA(insert ( 4054 23 20 4 3386 ));
DATA(insert ( 4054 23 21 1 3383 ));
DATA(insert ( 4054 23 21 2 3384 ));
DATA(insert ( 4054 23 21 3 3385 ));
DATA(insert ( 4054 23 21 4 3386 ));
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
/* minmax text */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4056 25 25 1 3383 ));
DATA(insert ( 4056 25 25 2 3384 ));
DATA(insert ( 4056 25 25 3 3385 ));
DATA(insert ( 4056 25 25 4 3386 ));
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
/* minmax oid */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4068 26 26 1 3383 ));
DATA(insert ( 4068 26 26 2 3384 ));
DATA(insert ( 4068 26 26 3 3385 ));
DATA(insert ( 4068 26 26 4 3386 ));
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
/* minmax tid */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4069 27 27 1 3383 ));
DATA(insert ( 4069 27 27 2 3384 ));
DATA(insert ( 4069 27 27 3 3385 ));
DATA(insert ( 4069 27 27 4 3386 ));
/* minmax float */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4070 700 700 1 3383 ));
DATA(insert ( 4070 700 700 2 3384 ));
DATA(insert ( 4070 700 700 3 3385 ));
DATA(insert ( 4070 700 700 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4070 700 701 1 3383 ));
DATA(insert ( 4070 700 701 2 3384 ));
DATA(insert ( 4070 700 701 3 3385 ));
DATA(insert ( 4070 700 701 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4070 701 701 1 3383 ));
DATA(insert ( 4070 701 701 2 3384 ));
DATA(insert ( 4070 701 701 3 3385 ));
DATA(insert ( 4070 701 701 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4070 701 700 1 3383 ));
DATA(insert ( 4070 701 700 2 3384 ));
DATA(insert ( 4070 701 700 3 3385 ));
DATA(insert ( 4070 701 700 4 3386 ));
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
/* minmax abstime */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4072 702 702 1 3383 ));
DATA(insert ( 4072 702 702 2 3384 ));
DATA(insert ( 4072 702 702 3 3385 ));
DATA(insert ( 4072 702 702 4 3386 ));
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
/* minmax reltime */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4073 703 703 1 3383 ));
DATA(insert ( 4073 703 703 2 3384 ));
DATA(insert ( 4073 703 703 3 3385 ));
DATA(insert ( 4073 703 703 4 3386 ));
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
/* minmax macaddr */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4074 829 829 1 3383 ));
DATA(insert ( 4074 829 829 2 3384 ));
DATA(insert ( 4074 829 829 3 3385 ));
DATA(insert ( 4074 829 829 4 3386 ));
/* minmax macaddr8 */
DATA(insert ( 4109 774 774 1 3383 ));
DATA(insert ( 4109 774 774 2 3384 ));
DATA(insert ( 4109 774 774 3 3385 ));
DATA(insert ( 4109 774 774 4 3386 ));
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
/* minmax inet */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4075 869 869 1 3383 ));
DATA(insert ( 4075 869 869 2 3384 ));
DATA(insert ( 4075 869 869 3 3385 ));
DATA(insert ( 4075 869 869 4 3386 ));
/* inclusion inet */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4102 869 869 1 4105 ));
DATA(insert ( 4102 869 869 2 4106 ));
DATA(insert ( 4102 869 869 3 4107 ));
DATA(insert ( 4102 869 869 4 4108 ));
DATA(insert ( 4102 869 869 11 4063 ));
DATA(insert ( 4102 869 869 12 4071 ));
DATA(insert ( 4102 869 869 13 930 ));
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
/* minmax character */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4076 1042 1042 1 3383 ));
DATA(insert ( 4076 1042 1042 2 3384 ));
DATA(insert ( 4076 1042 1042 3 3385 ));
DATA(insert ( 4076 1042 1042 4 3386 ));
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
/* minmax time without time zone */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4077 1083 1083 1 3383 ));
DATA(insert ( 4077 1083 1083 2 3384 ));
DATA(insert ( 4077 1083 1083 3 3385 ));
DATA(insert ( 4077 1083 1083 4 3386 ));
/* minmax datetime (date, timestamp, timestamptz) */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4059 1114 1114 1 3383 ));
DATA(insert ( 4059 1114 1114 2 3384 ));
DATA(insert ( 4059 1114 1114 3 3385 ));
DATA(insert ( 4059 1114 1114 4 3386 ));
DATA(insert ( 4059 1114 1184 1 3383 ));
DATA(insert ( 4059 1114 1184 2 3384 ));
DATA(insert ( 4059 1114 1184 3 3385 ));
DATA(insert ( 4059 1114 1184 4 3386 ));
DATA(insert ( 4059 1114 1082 1 3383 ));
DATA(insert ( 4059 1114 1082 2 3384 ));
DATA(insert ( 4059 1114 1082 3 3385 ));
DATA(insert ( 4059 1114 1082 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4059 1184 1184 1 3383 ));
DATA(insert ( 4059 1184 1184 2 3384 ));
DATA(insert ( 4059 1184 1184 3 3385 ));
DATA(insert ( 4059 1184 1184 4 3386 ));
DATA(insert ( 4059 1184 1114 1 3383 ));
DATA(insert ( 4059 1184 1114 2 3384 ));
DATA(insert ( 4059 1184 1114 3 3385 ));
DATA(insert ( 4059 1184 1114 4 3386 ));
DATA(insert ( 4059 1184 1082 1 3383 ));
DATA(insert ( 4059 1184 1082 2 3384 ));
DATA(insert ( 4059 1184 1082 3 3385 ));
DATA(insert ( 4059 1184 1082 4 3386 ));
2015-05-24 03:35:49 +02:00
DATA(insert ( 4059 1082 1082 1 3383 ));
DATA(insert ( 4059 1082 1082 2 3384 ));
DATA(insert ( 4059 1082 1082 3 3385 ));
DATA(insert ( 4059 1082 1082 4 3386 ));
DATA(insert ( 4059 1082 1114 1 3383 ));
DATA(insert ( 4059 1082 1114 2 3384 ));
DATA(insert ( 4059 1082 1114 3 3385 ));
DATA(insert ( 4059 1082 1114 4 3386 ));
DATA(insert ( 4059 1082 1184 1 3383 ));
DATA(insert ( 4059 1082 1184 2 3384 ));
DATA(insert ( 4059 1082 1184 3 3385 ));
DATA(insert ( 4059 1082 1184 4 3386 ));
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
/* minmax interval */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4078 1186 1186 1 3383 ));
DATA(insert ( 4078 1186 1186 2 3384 ));
DATA(insert ( 4078 1186 1186 3 3385 ));
DATA(insert ( 4078 1186 1186 4 3386 ));
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
/* minmax time with time zone */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4058 1266 1266 1 3383 ));
DATA(insert ( 4058 1266 1266 2 3384 ));
DATA(insert ( 4058 1266 1266 3 3385 ));
DATA(insert ( 4058 1266 1266 4 3386 ));
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
/* minmax bit */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4079 1560 1560 1 3383 ));
DATA(insert ( 4079 1560 1560 2 3384 ));
DATA(insert ( 4079 1560 1560 3 3385 ));
DATA(insert ( 4079 1560 1560 4 3386 ));
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
/* minmax bit varying */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4080 1562 1562 1 3383 ));
DATA(insert ( 4080 1562 1562 2 3384 ));
DATA(insert ( 4080 1562 1562 3 3385 ));
DATA(insert ( 4080 1562 1562 4 3386 ));
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
/* minmax numeric */
2015-05-24 03:35:49 +02:00
DATA(insert ( 4055 1700 1700 1 3383 ));
DATA(insert ( 4055 1700 1700 2 3384 ));
DATA(insert ( 4055 1700 1700 3 3385 ));
DATA(insert ( 4055 1700 1700 4 3386 ));
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.
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/* minmax uuid */
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DATA(insert ( 4081 2950 2950 1 3383 ));
DATA(insert ( 4081 2950 2950 2 3384 ));
DATA(insert ( 4081 2950 2950 3 3385 ));
DATA(insert ( 4081 2950 2950 4 3386 ));
/* inclusion range types */
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DATA(insert ( 4103 3831 3831 1 4105 ));
DATA(insert ( 4103 3831 3831 2 4106 ));
DATA(insert ( 4103 3831 3831 3 4107 ));
DATA(insert ( 4103 3831 3831 4 4108 ));
DATA(insert ( 4103 3831 3831 11 4057 ));
DATA(insert ( 4103 3831 3831 13 3859 ));
DATA(insert ( 4103 3831 3831 14 3850 ));
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.
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/* minmax pg_lsn */
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DATA(insert ( 4082 3220 3220 1 3383 ));
DATA(insert ( 4082 3220 3220 2 3384 ));
DATA(insert ( 4082 3220 3220 3 3385 ));
DATA(insert ( 4082 3220 3220 4 3386 ));
/* inclusion box */
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DATA(insert ( 4104 603 603 1 4105 ));
DATA(insert ( 4104 603 603 2 4106 ));
DATA(insert ( 4104 603 603 3 4107 ));
DATA(insert ( 4104 603 603 4 4108 ));
DATA(insert ( 4104 603 603 11 4067 ));
DATA(insert ( 4104 603 603 13 187 ));
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.
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#endif /* PG_AMPROC_H */