GreenPlum 7.1.0新特性介绍

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发布于 2024-02-26 15:28:43

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发布于 2024-02-26 15:28:43

文章被收录于专栏：小麦苗的DB宝专栏

简介

GreenPlum 7.0.0于2023-09-28发布，大约半年后，GreenPlum 7.1.0于2024-02-09发布。

在本文中，麦老师就其中一些比较实用的新特性做一些简单说明。

GreenPlum 7.1.0环境准备

docker rm -f gpdb7
docker run -itd --name gpdb7 -h gpdb7 \
  -p 5437:5432 -p 28087:28080  \
  -v /sys/fs/cgroup:/sys/fs/cgroup \
  --privileged=true lhrbest/greenplum:7.1.0 \
  /usr/sbin/init

docker exec -it gpdb7 bash
su - gpadmin
gpstart -a
gpcc start

gpcc status
gpstate

此docker包括1个master，1个standby master，2个segment，2个mirror实例；还包括gpcc 7.0.0

新特性实验

VMware Greenplum 7.1.0引入了tablefunc模块，提供了各种返回表的函数示例，包括行转列等功能

tablefunc模块包括多个返回表（也就是多行）的函数。这些函数都很有用，并且也可以作为如何编写返回多行的 C 函数的例子。

示例可以参考：https://www.postgresql.org/docs/12/tablefunc.html

http://postgres.cn/docs/12/tablefunc.html

函数	返回	描述
normal_rand(int numvals, float8 mean, float8 stddev)	setof float8	产生一个正态分布的随机值集合
crosstab(text sql)	setof record	产生一个包含行名称外加N个值列的“数据透视表”，其中N由调用查询中指定的行类型决定
crosstabN(text sql)	setof table_crosstab_N	产生一个包含行名称外加N个值列的“数据透视表”。crosstab2、crosstab3和crosstab4是被预定义的，但你可以按照下文所述创建额外的crosstabN函数
crosstab(text source_sql, text category_sql)	setof record	产生一个“数据透视表”，其值列由第二个查询指定
crosstab(text sql, int N)	setof record	crosstab(text)的废弃版本。参数N现在被忽略，因为值列的数量总是由调用查询所决定
connectby(text relname, text keyid_fld, text parent_keyid_fld [, text orderby_fld ], text start_with, int max_depth [, text branch_delim ])	setof record	产生一个层次树结构的表达

db1=# CREATE EXTENSION tablefunc;
CREATE EXTENSION
db1=# SELECT * FROM normal_rand(1000, 5, 3);
     normal_rand      
----------------------
   2.3210274434791187
    1.231076402857033
  -0.8117263529261152
  -1.2934824713330597
    8.292221876591267
    3.804515144372151
   1.9176029752768766
    7.146218652634886
    3.551605912228543
    5.575493201208664
    6.666709079414525
   2.5228426084040176
    6.407538689302069
   5.8016036456658995
    4.277014091604118
    5.780894470091546
    5.750904724932745
    5.753381245096707
   2.4427467584795792
     6.81576512005292
    8.192744936276732
    6.614708709243898
     8.77794265411034
    5.791113475048419
     5.70369412214234
    4.327753473864319
    7.570550167961118
   3.5597661002608407
    8.046435727461073
    9.658108512543121
    6.470092796527577
    7.666408022086054
db1=# 
db1=# 
db1=# 
db1=# CREATE TABLE ct(id SERIAL, rowid TEXT, attribute TEXT, value TEXT);
NOTICE:  Table doesn't have 'DISTRIBUTED BY' clause -- Using column named 'id' as the Greenplum Database data distribution key for this table.
HINT:  The 'DISTRIBUTED BY' clause determines the distribution of data. Make sure column(s) chosen are the optimal data distribution key to minimize skew.
INSERT INTO ct(rowid, attribute, value) VALUES('test1','att1','val1');
CREATE TABLE
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test1','att1','val1');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test1','att2','val2');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test1','att3','val3');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test1','att4','val4');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test2','att1','val5');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test2','att2','val6');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test2','att3','val7');
INSERT 0 1
db1=# INSERT INTO ct(rowid, attribute, value) VALUES('test2','att4','val8');
INSERT 0 1
db1=# 
db1=# SELECT *
db1-# FROM crosstab(
db1(#   'select rowid, attribute, value
db1'#    from ct
db1'#    where attribute = ''att2'' or attribute = ''att3''
db1'#    order by 1,2')
db1-# AS ct(row_name text, category_1 text, category_2 text, category_3 text);
 row_name | category_1 | category_2 | category_3 
----------+------------+------------+------------
 test1    | val2       | val3       | 
 test2    | val6       | val7       | 
(2 rows)

db1=# create table sales(year int, month int, qty int);
NOTICE:  Table doesn't have 'DISTRIBUTED BY' clause -- Using column named 'year' as the Greenplum Database data distribution key for this table.
HINT:  The 'DISTRIBUTED BY' clause determines the distribution of data. Make sure column(s) chosen are the optimal data distribution key to minimize skew.
CREATE TABLE
db1=# insert into sales values(2007, 1, 1000);
INSERT 0 1
db1=# insert into sales values(2007, 2, 1500);
INSERT 0 1
db1=# insert into sales values(2007, 7, 500);
INSERT 0 1
db1=# insert into sales values(2007, 11, 1500);
INSERT 0 1
db1=# insert into sales values(2007, 12, 2000);
INSERT 0 1
db1=# insert into sales values(2008, 1, 1000);
INSERT 0 1
db1=# 
db1=# select * from crosstab(
db1(#   'select year, month, qty from sales order by 1',
db1(#   'select m from generate_series(1,12) m'
db1(# ) as (
db1(#   year int,
db1(#   "Jan" int,
db1(#   "Feb" int,
db1(#   "Mar" int,
db1(#   "Apr" int,
db1(#   "May" int,
db1(#   "Jun" int,
db1(#   "Jul" int,
db1(#   "Aug" int,
db1(#   "Sep" int,
db1(#   "Oct" int,
db1(#   "Nov" int,
db1(#   "Dec" int
db1(# );
 year | Jan  | Feb  | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov  | Dec  
------+------+------+-----+-----+-----+-----+-----+-----+-----+-----+------+------
 2007 | 1000 | 1500 |     |     |     |     | 500 |     |     |     | 1500 | 2000
 2008 | 1000 |      |     |     |     |     |     |     |     |     |      |     
(2 rows)

db1=# CREATE TABLE cth(rowid text, rowdt timestamp, attribute text, val text);
NOTICE:  Table doesn't have 'DISTRIBUTED BY' clause -- Using column named 'rowid' as the Greenplum Database data distribution key for this table.
HINT:  The 'DISTRIBUTED BY' clause determines the distribution of data. Make sure column(s) chosen are the optimal data distribution key to minimize skew.
CREATE TABLE
db1=# INSERT INTO cth VALUES('test1','01 March 2003','temperature','42');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test1','01 March 2003','test_result','PASS');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test1','01 March 2003','volts','2.6987');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test2','02 March 2003','temperature','53');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test2','02 March 2003','test_result','FAIL');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test2','02 March 2003','test_startdate','01 March 2003');
INSERT 0 1
db1=# INSERT INTO cth VALUES('test2','02 March 2003','volts','3.1234');
INSERT 0 1
db1=# 
db1=# SELECT * FROM crosstab
db1-# (
db1(#   'SELECT rowid, rowdt, attribute, val FROM cth ORDER BY 1',
db1(#   'SELECT DISTINCT attribute FROM cth ORDER BY 1'
db1(# )
db1-# AS
db1-# (
db1(#        rowid text,
db1(#        rowdt timestamp,
db1(#        temperature int4,
db1(#        test_result text,
db1(#        test_startdate timestamp,
db1(#        volts float8
db1(# );
 rowid |        rowdt        | temperature | test_result |   test_startdate    | volts  
-------+---------------------+-------------+-------------+---------------------+--------
 test1 | 2003-03-01 00:00:00 |          42 | PASS        |                     | 2.6987
 test2 | 2003-03-02 00:00:00 |          53 | FAIL        | 2003-03-01 00:00:00 | 3.1234
(2 rows)

db1=#

新增pg_buffercache和gp_buffercache视图

VMware Greenplum包括一个新的扩展程序 - pg_buffercache -，允许用户访问五个视图以获取集群范围的共享缓冲区指标：gp_buffercache、gp_buffercache_summary、gp_buffercache_usage_counts、gp_buffercache_summary_aggregated和gp_buffercache_usage_counts_aggregated。

该特性在GreenPlum 6.26.2中已提供，不过提供的视图较少。可以参考：https://www.xmmup.com/greenplum-6262banbenxintexingshuoming.html

[gpadmin@gpdb7 ~]$ psql
psql (12.12)
Type "help" for help.

postgres=#  select version();
                                                                                                                version                                                                                                                 
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 PostgreSQL 12.12 (Greenplum Database 7.1.0 build commit:e7c2b1f14bb42a1018ac57d14f4436880e0a0515) on x86_64-pc-linux-gnu, compiled by gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-18), 64-bit compiled on Jan 19 2024 06:39:45 Bhuvnesh C.
(1 row)

postgres=# create database db1;
CREATE DATABASE
postgres=# \c db1
You are now connected to database "db1" as user "gpadmin".
db1=# create extension pg_buffercache;
CREATE EXTENSION
db1=#  select count(*) from gp_buffercache;
 count 
-------
 12000
(1 row)

db1=#  select count(*) from pg_buffercache;
 count 
-------
  4000
(1 row)

db1=# select * from gp_buffercache limit 6;
 gp_segment_id | bufferid | relfilenode | reltablespace | reldatabase | relforknumber | relblocknumber | isdirty | usagecount | pinning_backends 
---------------+----------+-------------+---------------+-------------+---------------+----------------+---------+------------+------------------
            -1 |        1 |       13721 |          1664 |           0 |             0 |              0 | f       |          5 |                0
            -1 |        2 |        1259 |          1663 |       13720 |             0 |              0 | f       |          5 |                0
            -1 |        3 |        1259 |          1663 |       13720 |             0 |              1 | f       |          5 |                0
            -1 |        4 |        1249 |          1663 |       13720 |             0 |              0 | f       |          5 |                0
            -1 |        5 |        1249 |          1663 |       13720 |             0 |              1 | f       |          5 |                0
            -1 |        6 |        1249 |          1663 |       13720 |             0 |              2 | f       |          5 |                0
(6 rows)

db1=# 
db1=# SELECT n.nspname, c.relname, count(*) AS buffers
db1-#              FROM pg_buffercache b JOIN pg_class c
db1-#              ON b.relfilenode = pg_relation_filenode(c.oid) AND
db1-#                 b.reldatabase IN (0, (SELECT oid FROM pg_database
db1(#                                       WHERE datname = current_database()))
db1-#              JOIN pg_namespace n ON n.oid = c.relnamespace
db1-#              GROUP BY n.nspname, c.relname
db1-#              ORDER BY 3 DESC
db1-#              LIMIT 10;
  nspname   |            relname             | buffers 
------------+--------------------------------+---------
 pg_catalog | pg_proc                        |      14
 pg_catalog | pg_depend_reference_index      |      13
 pg_catalog | pg_attribute                   |      12
 pg_catalog | pg_depend                      |      11
 pg_catalog | pg_class                       |      11
 pg_catalog | pg_rewrite                     |       7
 pg_catalog | pg_type                        |       7
 pg_catalog | pg_proc_proname_args_nsp_index |       7
 pg_catalog | pg_init_privs                  |       6
 pg_catalog | pg_authid                      |       5
(10 rows)

db1=# select count(*) from gp_buffercache_summary;
 count 
-------
     3
(1 row)

db1=# select * from gp_buffercache_summary;
 gp_segment_id | buffers_used | buffers_unused | buffers_dirty | buffers_pinned |   usagecount_avg   
---------------+--------------+----------------+---------------+----------------+--------------------
            -1 |         1562 |           2438 |           120 |              0 |  3.881562099871959
             0 |         1489 |           2511 |           117 |              0 | 3.4976494291470788
             1 |         1493 |           2507 |           119 |              0 |  3.495646349631614
(3 rows)

db1=# select * from gp_buffercache_usage_counts;
 gp_segment_id | usage_count | buffers | dirty | pinned 
---------------+-------------+---------+-------+--------
            -1 |           0 |    2438 |     0 |      0
            -1 |           1 |     228 |     5 |      0
            -1 |           2 |     240 |     8 |      0
            -1 |           3 |      49 |     8 |      0
            -1 |           4 |      17 |     1 |      0
            -1 |           5 |    1028 |    98 |      0
             0 |           0 |    2509 |     0 |      0
             0 |           1 |     444 |     6 |      0
             0 |           2 |     123 |     6 |      0
             0 |           3 |      39 |     7 |      0
             0 |           4 |      17 |     2 |      0
             0 |           5 |     868 |    97 |      0
             1 |           0 |    2505 |     0 |      0
             1 |           1 |     446 |     6 |      0
             1 |           2 |     123 |     6 |      0
             1 |           3 |      39 |     7 |      0
             1 |           4 |      18 |     2 |      0
             1 |           5 |     869 |   100 |      0
(18 rows)

db1=# select * from gp_buffercache_summary_aggregated;
 buffers_used | buffers_unused | buffers_dirty | buffers_pinned |  usagecount_avg   
--------------+----------------+---------------+----------------+-------------------
         4550 |           7450 |           359 |              0 | 3.625432361146132
(1 row)

db1=# select * from gp_buffercache_usage_counts_aggregated;
 usage_count | buffers | dirty | pinned 
-------------+---------+-------+--------
          45 |   12000 |   359 |      0
(1 row)

db1=#

孤儿文件相关

gp_toolkit模式中的gp_check_orphaned_files视图包含一个新列 - filepath -，用于打印孤立文件的相对/绝对路径。

VMware Greenplum 7.1.0在gp_toolkit管理模式中添加了gp_move_orphaned_files用户定义函数(UDF)，该函数将gp_check_orphaned_files视图找到的孤立文件移动到您指定的文件系统位置。

参考：https://docs.vmware.com/en/VMware-Greenplum/7/greenplum-database/ref_guide-gp_toolkit.html#moveorphanfiles

分区表相关

gp_toolkit管理模式现在包括一些用于辅助分区维护的对象：一个新视图 - gp_partitions，以及几个新的用户定义函数，包括：pg_partition_rank()、pg_partition_range_from()、pg_partition_range_to()、pg_partition_bound_value()、pg_partition_isdefault()、pg_partition_lowest_child()和pg_partition_highest_child()。有关详细信息，请参阅gp_toolkit管理模式主题。

可以参考：https://docs.vmware.com/en/VMware-Greenplum/7/greenplum-database/ref_guide-gp_toolkit.html

pg_filedump程序

参考：https://docs.vmware.com/en/VMware-Greenplum/7/greenplum-database/utility_guide-ref-pg_filedump.html?hWord=N4IghgNiBcIA4HMD6AzAlhApgEwK4Fs4QBfIA

VMware Greenplum引入了一个新实用程序 - pg_filedump -，允许您读取格式化内容的VMware Greenplum数据文件，包括表、索引和控制文件。

The pg_filedump utility formats VMware Greenplum data files -- including table, index and control files -- into a human-readable format.

To use pg_filedump, you must have:

gpsupport 1.0.3 or higher installed
a search path that includes the gpsupport executable path

NOTE pg_filedump is currently only supported for Greenplum 7 data files.

[gpadmin@gpdb7 18444]$ pg_filedump 9926

*******************************************************************
* PostgreSQL File/Block Formatted Dump Utility
*
* File: 9926
* Options used: None
*******************************************************************

Block    0 ********************************************************
<Header> -----
 Block Offset: 0x00000000         Offsets: Lower      64 (0x0040)
 Block: Size 32768  Version   14            Upper    32752 (0x7ff0)
 LSN:  logid      0 recoff 0x046f5240      Special  32752 (0x7ff0)
 Items:   10                      Free Space: 32688
 Checksum: 0x0496  Prune XID: 0x00000000  Flags: 0x0000 ()
 Length (including item array): 64

 BTree Meta Data:  Magic (0x00053162)   Version (4)
                   Root:     Block (0)  Level (0)
                   FastRoot: Block (0)  Level (0)

<Special Section> -----
 BTree Index Section:
  Flags: 0x0008 (META)
  Blocks: Previous (0)  Next (0)  Level (0)  CycleId (0)


*** End of File Encountered. Last Block Read: 0 ***

[gpadmin@gpdb7 mirror]$ find ./ -name pg_control
./gpseg0/global/pg_control
./gpseg1/global/pg_control

[gpadmin@gpdb7 mirror]$ pg_filedump -c ./gpseg0/global/pg_control

*******************************************************************
* PostgreSQL File/Block Formatted Dump Utility
*
* File: ./gpseg0/global/pg_control
* Options used: -c
*******************************************************************

<pg_control Contents> *********************************************

                          CRC: Correct
           pg_control Version: 12010700
              Catalog Version: 302307241
            System Identifier: 7287791898375007577
                        State: IN ARCHIVE RECOVERY
                Last Mod Time: Sun Feb 18 11:11:48 2024
       Last Checkpoint Record: Log File (0) Offset (0x0cf18ca8)
  Last Checkpoint Record Redo: Log File (0) Offset (0x0cf18b50)
          |-       TimeLineID: 1
          |-         Next XID: 0/2060
          |-         Next OID: 26549
          |- Next Relfilenode: 25699
          |-       Next Multi: 1
          |-    Next MultiOff: 0
          |-             Time: Sun Feb 18 11:11:48 2024
       Minimum Recovery Point: Log File (0) Offset (0x0cfa18c0)
          Backup Start Record: Log File (0) Offset (0x00000000)
            Backup End Record: Log File (0) Offset (0x00000000)
End-of-Backup Record Required: no
       Maximum Data Alignment: 8
        Floating-Point Sample: 1234567
          Database Block Size: 32768
           Blocks Per Segment: 32768
              XLOG Block Size: 32768
            XLOG Segment Size: 67108864
    Maximum Identifier Length: 64
           Maximum Index Keys: 32
             TOAST Chunk Size: 8140

故障恢复gprecoverseg

当使用输入配置文件（gprecoverseg -i）时，VMware Greenplum现在支持差异段恢复。此外，您现在可以在传递给gprecoverseg -i的recover_config_file中的条目之前添加I、D或F来指示段恢复的类型。在 GreenPlum 6.25.0中也提供了差异化恢复

recoveryType field supports below values:
    I/i for incremental recovery
    D/d for differential recovery
    F/f for full recovery

EXPLAIN ANALYZE增强

当使用BUFFERS关键字时，EXPLAIN ANALYZE现在显示缓冲区使用情况和I/O时间。

postgres=# \h explain analyze
Command:     EXPLAIN
Description: show the execution plan of a statement
Syntax:
EXPLAIN [ ( option [, ...] ) ] statement
EXPLAIN [ ANALYZE ] [ VERBOSE ] statement

where option can be one of:

    ANALYZE [ boolean ]
    VERBOSE [ boolean ]
    COSTS [ boolean ]
    SETTINGS [ boolean ]
    BUFFERS [ boolean ]
    TIMING [ boolean ]
    SUMMARY [ boolean ]
    FORMAT { TEXT | XML | JSON | YAML }

URL: https://www.postgresql.org/docs/12/sql-explain.html


postgres=#  EXPLAIN (ANALYZE) select * from pg_tables;
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Hash Left Join  (cost=2.25..19.63 rows=91 width=260) (actual time=0.181..0.407 rows=91 loops=1)
   Hash Cond: (c.reltablespace = t.oid)
   Extra Text: Hash chain length 1.0 avg, 1 max, using 2 of 65536 buckets.
   ->  Hash Left Join  (cost=1.20..17.15 rows=91 width=140) (actual time=0.114..0.280 rows=91 loops=1)
         Hash Cond: (c.relnamespace = n.oid)
         Extra Text: Hash chain length 1.0 avg, 1 max, using 9 of 65536 buckets.
         ->  Seq Scan on pg_class c  (cost=0.00..14.80 rows=91 width=80) (actual time=0.043..0.125 rows=91 loops=1)
               Filter: (relkind = ANY ('{r,p}'::"char"[]))
               Rows Removed by Filter: 533
         ->  Hash  (cost=1.09..1.09 rows=9 width=68) (actual time=0.009..0.010 rows=9 loops=1)
               Buckets: 65536  Batches: 1  Memory Usage: 513kB
               ->  Seq Scan on pg_namespace n  (cost=0.00..1.09 rows=9 width=68) (actual time=0.004..0.005 rows=9 loops=1)
   ->  Hash  (cost=1.02..1.02 rows=2 width=68) (actual time=0.004..0.004 rows=2 loops=1)
         Buckets: 65536  Batches: 1  Memory Usage: 513kB
         ->  Seq Scan on pg_tablespace t  (cost=0.00..1.02 rows=2 width=68) (actual time=0.002..0.003 rows=2 loops=1)
 Optimizer: Postgres-based planner
 Planning Time: 0.783 ms
   (slice0)    Executor memory: 1131K bytes.  Work_mem: 513K bytes max.
 Memory used:  128000kB
 Execution Time: 0.462 ms
(20 rows)



postgres=# EXPLAIN (ANALYZE, BUFFERS) select * from pg_tables;
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Hash Left Join  (cost=2.25..19.63 rows=91 width=260) (actual time=0.438..0.726 rows=91 loops=1)
   Hash Cond: (c.reltablespace = t.oid)
   Extra Text: Hash chain length 1.0 avg, 1 max, using 2 of 65536 buckets.
   Buffers: shared hit=9
   ->  Hash Left Join  (cost=1.20..17.15 rows=91 width=140) (actual time=0.149..0.341 rows=91 loops=1)
         Hash Cond: (c.relnamespace = n.oid)
         Extra Text: Hash chain length 1.0 avg, 1 max, using 9 of 65536 buckets.
         Buffers: shared hit=8
         ->  Seq Scan on pg_class c  (cost=0.00..14.80 rows=91 width=80) (actual time=0.060..0.140 rows=91 loops=1)
               Filter: (relkind = ANY ('{r,p}'::"char"[]))
               Rows Removed by Filter: 533
               Buffers: shared hit=7
         ->  Hash  (cost=1.09..1.09 rows=9 width=68) (actual time=0.012..0.013 rows=9 loops=1)
               Buckets: 65536  Batches: 1  Memory Usage: 513kB
               Buffers: shared hit=1
               ->  Seq Scan on pg_namespace n  (cost=0.00..1.09 rows=9 width=68) (actual time=0.005..0.006 rows=9 loops=1)
                     Buffers: shared hit=1
   ->  Hash  (cost=1.02..1.02 rows=2 width=68) (actual time=0.006..0.006 rows=2 loops=1)
         Buckets: 65536  Batches: 1  Memory Usage: 513kB
         Buffers: shared hit=1
         ->  Seq Scan on pg_tablespace t  (cost=0.00..1.02 rows=2 width=68) (actual time=0.003..0.004 rows=2 loops=1)
               Buffers: shared hit=1
 Optimizer: Postgres-based planner
 Planning Time: 0.878 ms
   (slice0)    Executor memory: 1131K bytes.  Work_mem: 513K bytes max.
 Memory used:  128000kB
 Execution Time: 0.811 ms
(27 rows)

gppkg增强

gppkg实用程序选项 -f 现在可帮助删除具有不完整或缺失文件的软件包。

[gpadmin@gpdb7 gppkg]$ gppkg install MetricsCollector-7.0.0_gp_7.0.0-rocky8-x86_64.gppkg 
Detecting network topology:    [==============================================================] [OK]
2 coordinators and 4 segment instances are detected on 1 unique host.
Distributing package:          [==============================================================] [OK]
Decoding package:              [==============================================================] [OK]
Verifying package installation:[==============================================================] [OK]
Verifying package integrity:   [==============================================================] [OK]
You are going to install the following packages:
        Install 'MetricsCollector@7.0.0_gp_7.0.0'
Continue? [y/N] y
Allocating disk space:         [================X                                          ] [ERROR]
Cleanup:                       [==============================================================] [OK]
Error: from gpdb7: IoError(file '/usr/local/greenplum-db-7.1.0/lib/postgresql/metrics_collector.so' exists in the filesystem

Caused by:
    entity already exists)


[gpadmin@gpdb7 gppkg]$ ll /usr/local/greenplum-db-7.1.0/lib/postgresql/metrics_collector.so
-rwxr-xr-x 1 gpadmin gpadmin 3570904 Jan 31 14:51 /usr/local/greenplum-db-7.1.0/lib/postgresql/metrics_collector.so


[gpadmin@gpdb7 gppkg]$ gppkg install MetricsCollector-7.0.0_gp_7.0.0-rocky8-x86_64.gppkg  -f
Detecting network topology:    [==============================================================] [OK]
2 coordinators and 4 segment instances are detected on 1 unique host.
Distributing package:          [==============================================================] [OK]
Decoding package:              [==============================================================] [OK]
Verifying package installation:[==============================================================] [OK]
Verifying package integrity:   [==============================================================] [OK]
You are going to install the following packages:
        Install 'MetricsCollector@7.0.0_gp_7.0.0'
Continue? [y/N] y
Allocating disk space:         [==============================================================] [OK]
Install 'MetricsCollector':    [==============================================================] [OK]
The stdout from the script of the post-install:                                                ] 0.0
-
==========================================================================
Metrics Collector installation is complete!
==========================================================================


Running post-install hook:     [==============================================================] [OK]
Result:
        MetricsCollector has been successfully installed
Clean Up:                      [==============================================================] [OK]

系统视图gp_stat_progress_dtx_recovery

系统视图gp_stat_progress_dtx_recovery显示了分布式事务（DTX）恢复过程的进度，这可能对监视协调器崩溃后的恢复状态很有用。

[gpadmin@gpdb7 ~]$ ps -ef|grep post | grep bin
gpadmin     1204       1  0 10:15 ?        00:00:01 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/primary/gpseg0 -c gp_role=execute
gpadmin     1209       1  0 10:15 ?        00:00:01 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/primary/gpseg1 -c gp_role=execute
gpadmin     1243       0  0 10:15 ?        00:00:01 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/master/gpseg-1 -c gp_role=dispatch
gpadmin     1393       1  0 10:15 ?        00:00:00 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/master_standby/gpseg-1 -c gp_role=dispatch
gpadmin     4525       1  0 10:16 ?        00:00:00 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/mirror/gpseg0 -c gp_role=execute
gpadmin     4526       1  0 10:16 ?        00:00:00 /usr/local/greenplum-db-7.1.0/bin/postgres -D /opt/greenplum/data/mirror/gpseg1 -c gp_role=execute
[gpadmin@gpdb7 ~]$ kill -9 1209
[gpadmin@gpdb7 ~]$ psql
psql (12.12)
Type "help" for help.

postgres=# select * from gp_stat_progress_dtx_recovery;
 phase | recover_commited_dtx_total | recover_commited_dtx_completed | in_doubt_tx_total | in_doubt_tx_in_progress | in_doubt_tx_aborted 
-------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------
(0 rows)

postgres=# select * from gp_stat_progress_dtx_recovery;
                  phase                   | recover_commited_dtx_total | recover_commited_dtx_completed | in_doubt_tx_total | in_doubt_tx_in_progress | in_doubt_tx_aborted 
------------------------------------------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------
 gathering in-doubt orphaned transactions |                          0 |                              0 |                 0 |                       0 |                   0
(1 row)

postgres=# select * from gp_stat_progress_dtx_recovery;
 phase | recover_commited_dtx_total | recover_commited_dtx_completed | in_doubt_tx_total | in_doubt_tx_in_progress | in_doubt_tx_aborted 
-------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------
(0 rows)
postgres=# select * from gp_segment_configuration ;
 dbid | content | role | preferred_role | mode | status | port | hostname | address |                  datadir                   
------+---------+------+----------------+------+--------+------+----------+---------+--------------------------------------------
    1 |      -1 | p    | p              | n    | u      | 5432 | gpdb7    | gpdb7   | /opt/greenplum/data/master/gpseg-1
    3 |       1 | m    | p              | n    | d      | 6001 | gpdb7    | gpdb7   | /opt/greenplum/data/primary/gpseg1
    5 |       1 | p    | m              | n    | u      | 7001 | gpdb7    | gpdb7   | /opt/greenplum/data/mirror/gpseg1
    6 |      -1 | m    | m              | s    | u      | 5433 | gpdb7    | gpdb7   | /opt/greenplum/data/master_standby/gpseg-1
    2 |       0 | p    | p              | s    | u      | 6000 | gpdb7    | gpdb7   | /opt/greenplum/data/primary/gpseg0
    4 |       0 | m    | m              | s    | u      | 7000 | gpdb7    | gpdb7   | /opt/greenplum/data/mirror/gpseg0
(6 rows)

postgres=#

log_directory配置日志位置

您现在可以使用服务器配置参数log_directory手动配置VMware Greenplum日志的位置。gpsupport实用程序还支持从由此服务器配置参数设置的目录中收集日志。

-- GPDB 7.1.0 ，日志默认位于log目录，/opt/greenplum/data/master/gpseg-1/log/
[gpadmin@gpdb7 ~]$ gpconfig -s log_directory
Values on all segments are consistent
GUC              : log_directory
Coordinator value: log
Segment     value: log

-- GPDB 6.26，日志默认位于pg_log目录
[gpadmin@gpdb6261 ~]$ gpconfig -s log_directory
Values on all segments are consistent
GUC          : log_directory
Master  value: pg_log
Segment value: pg_log
[gpadmin@gpdb6261 ~]$

新增optimizer_enable_right_outer_join服务器配置参数

新的optimizer_enable_right_outer_join服务器配置参数允许您控制GPORCA是否生成右外连接。在观察到与右外连接相关的性能不佳的情况下，您可以选择禁止使用它们。 该特性在GreenPlum 6.26.2中已提供。可以参考：https://www.xmmup.com/greenplum-6262banbenxintexingshuoming.html

[gpadmin@gpdb7 ~]$ gpconfig -s optimizer_enable_right_outer_join
Values on all segments are consistent
GUC              : optimizer_enable_right_outer_join
Coordinator value: on
Segment     value: on
[gpadmin@gpdb7 ~]$

VACUUM命令现在包含了SKIP_DATABASE_STATS和ONLY_DATABASE_STATS子句

postgres=# \h vacuum
Command:     VACUUM
Description: garbage-collect and optionally analyze a database
Syntax:
VACUUM [ ( option [, ...] ) ] [ table_and_columns [, ...] ]
VACUUM [ FULL ] [ FREEZE ] [ VERBOSE ] [ AO_AUX_ONLY ]  [ ANALYZE ] [ table_and_columns [, ...] ]

where option can be one of:

    FULL [ boolean ]
    FREEZE [ boolean ]
    VERBOSE [ boolean ]
    AO_AUX_ONLY [ boolean ]
    ANALYZE [ boolean ]
    DISABLE_PAGE_SKIPPING [ boolean ]
    SKIP_LOCKED [ boolean ]
    INDEX_CLEANUP [ boolean ]
    TRUNCATE [ boolean ]
    SKIP_DATABASE_STATS [ boolean ]
    ONLY_DATABASE_STATS [ boolean ]

and table_and_columns is:

    table_name [ ( column_name [, ...] ) ]

URL: https://www.postgresql.org/docs/12/sql-vacuum.html

pg_config命令的输出现在包括了Greenplum版本信息。

[gpadmin@gpdb7 ~]$ which pg_config
/usr/local/greenplum-db-7.1.0/bin/pg_config
[gpadmin@gpdb7 ~]$ pg_config 
BINDIR = /usr/local/greenplum-db-7.1.0/bin
DOCDIR = /usr/local/greenplum-db-7.1.0/share/doc/postgresql
HTMLDIR = /usr/local/greenplum-db-7.1.0/share/doc/postgresql
INCLUDEDIR = /usr/local/greenplum-db-7.1.0/include
PKGINCLUDEDIR = /usr/local/greenplum-db-7.1.0/include/postgresql
INCLUDEDIR-SERVER = /usr/local/greenplum-db-7.1.0/include/postgresql/server
LIBDIR = /usr/local/greenplum-db-7.1.0/lib
PKGLIBDIR = /usr/local/greenplum-db-7.1.0/lib/postgresql
LOCALEDIR = /usr/local/greenplum-db-7.1.0/share/locale
MANDIR = /usr/local/greenplum-db-7.1.0/man
SHAREDIR = /usr/local/greenplum-db-7.1.0/share/postgresql
SYSCONFDIR = /usr/local/greenplum-db-7.1.0/etc/postgresql
PGXS = /usr/local/greenplum-db-7.1.0/lib/postgresql/pgxs/src/makefiles/pgxs.mk
CONFIGURE = '--with-gssapi' '--enable-orafce' '--enable-orca' '--enable-gpcloud' '--with-libxml' '--with-openssl' '--with-pam' '--with-ldap' '--with-uuid=e2fs' '--with-llvm' '--with-pgport=5432' '--disable-debug-extensions' '--disable-tap-tests' '--enable-ic-proxy' '--with-perl' '--with-python' 'PYTHON=python3.9' '--with-includes=/tmp/build/60664f00/gpdb_src/gpAux/ext/rocky8_x86_64/include /tmp/build/60664f00/gpdb_src/gpAux/ext/rocky8_x86_64/include/libxml2' '--with-libraries=/tmp/build/60664f00/gpdb_src/gpAux/ext/rocky8_x86_64/lib' '--disable-rpath' 'LDFLAGS=-Wl,--enable-new-dtags -Wl,-rpath,$ORIGIN/../lib' '--prefix=/usr/local/greenplum-db-devel' '--mandir=/usr/local/greenplum-db-devel/man' 'CFLAGS=-O3 -fargument-noalias-global -fno-omit-frame-pointer -g' 'PKG_CONFIG_PATH=/usr/local/lib64/pkgconfig'
CC = gcc
CPPFLAGS = -D_GNU_SOURCE -I/usr/include/libxml2
CFLAGS = -Wall -Wmissing-prototypes -Wpointer-arith -Werror=vla -Wendif-labels -Wmissing-format-attribute -Wformat-security -fno-strict-aliasing -fwrapv -fexcess-precision=standard -Wno-unused-but-set-variable -Werror=implicit-fallthrough=3 -Wno-format-truncation -Wno-stringop-truncation -O3 -fargument-noalias-global -fno-omit-frame-pointer -g  -Werror=uninitialized -Werror=implicit-function-declaration
CFLAGS_SL = -fPIC
LDFLAGS = -Wl,--enable-new-dtags -Wl,-rpath,$ORIGIN/../lib -L/usr/lib64 -Wl,--as-needed
LDFLAGS_EX = 
LDFLAGS_SL = 
LIBS = -lpgcommon -lpgport -lpthread -lxerces-c -lbz2 -lxml2 -lpam -lrt -lssl -lcrypto -lgssapi_krb5 -luv -lz -lreadline -lrt -lcrypt -ldl -lm  -lcurl -L/usr/lib -lzstd 
VERSION = PostgreSQL 12.12
GP_VERSION = Greenplum 7.1.0 build commit:e7c2b1f14bb42a1018ac57d14f4436880e0a0515
[gpadmin@gpdb7 ~]$

全部新特性原文

Release 7.1.0

Release Date: 2024-02-09

VMware Greenplum 7.1.0 is a minor release that includes new and changed features and resolves several issues.

New and Changed Features

VMware Greenplum 7.1.0 includes these new and changed features:

The pgvector module was updated to version 0.5.1. Refer to pgvector for module and upgrade information.
The ip4r module was updated to version 2.4.2. See ip4r.
VMware Greenplum 7.1.0 introduces the tablefunc module, which provides various examples of functions that return tables.
VMWware Greenplum includes a new extension - pg_buffercache -- which gives users access to five views to obtain clusterwide shared buffer metrics: gp_buffercache, gp_buffercache_summary, gp_buffercache_usage_counts, gp_buffercache_summary_aggregated, and gp_buffercache_usage_counts_aggregated.
VMware Greenplum 7.1.0 adds the gp_move_orphaned_files user-defined function (UDF) to the gp_toolkit administrative schema, which moves orphaned files found by the gp_check_orphaned_files view into a file system location that you specify.
The gp_check_orphaned_files view in the gp_toolkit schema contains a new column - filepath -- which prints relative/absolute path of the orphaned file.
Greenplum package utility, gppkg, introduces a new option to specify the name of the package to migrate to another minor version of VMware Greenplum, instead of migrating all packages.
The gp_toolkit administrative schema now includes some objects to aid in partition maintenance: a new view -- gp_partitions, and several new user-defined functions, including: pg_partition_rank(), pg_partition_range_from(), pg_partition_range_to(), pg_partition_bound_value(), pg_partition_isdefault(), pg_partition_lowest_child(), and pg_partition_highest_child(). See The gp_toolkit Administrative Schema topic for details.
VMware Greenplum introduces a new utility -- pg_filedump -- which allows you to read formatted content of VMware Greenplum data files, including table, index and control files.
Query optimization has been fine tuned to enhance performance for queries containing multiple DQA (Distinct Qualified Aggregate) and standard aggregates. This refinement leads to substantial IO savings, resulting in improved processing speed. This optimization may not be applicable for certain specialized queries, such as scenarios in which there are multiple columns from different DQA sources within a standard aggregate, or when filters are present within the DQA.
The new gp_postmaster_address_family server configuration parameter tells a node which type of IP address to use when initializing a cluster.
Greenplum's Data Science Package for Python now includes the catboost library, a high-performance open source library for gradient boosting on decision trees.
VMware Greenplum now supports differential segment recovery when using input configuration files (gprecoverseg -i). In addition, you may now prepend an I, D, or F to an entry in the recover_config_file you pass to gprecoverseg -i to indicate the type of segment recovery.
EXPLAIN ANALYZE now shows buffer usage and I/O timings when using the BUFFERS keyword.
The gpstate utility now tracks data synchronization for a differential recovery with the -e option.
VMware Greenplum now supports the TABLESAMPLE clause for append-optimized tables, in addition to heap tables. Both BERNOULLI and SYSTEM sampling methods are now supported.
VMware Greenplum now supports the SYSTEM_ROWS and SYSTEM_TIME sampling methods for all tables, made available through the new tsm_system_rows and tsm_system_time modules, respectively.
The gppkg utility option -f now helps remove packages which have incomplete or missing files.
The PgBouncer connection pooler 1.21.0 is now distributed with VMware Greenplum 7.1.0, which includes support for encrypted LDAP passwords. Refer to Using the PgBouncer Connection Pooler for more details.
The new gprecoverseg option max-rate allows you to limit the maximum transfer bandwidth rate for a full segment recovery.
The gpmovemirrors utility has a new disk space check, so the utility will fail if the target host does not have enough space to accommodate the new mirrors.
Autovacuum now drops any orphaned temporary tables not dropped by the backends they were created on.
You may manually configure the location of your VMware Greenplum logs with the server configuration parameter log_directory. The gpsupport utility also supports collecting the logs from the directory set by this server configuration parameter.
The system view gp_stat_progress_dtx_recovery displays the progress of the Distributed Transaction (DTX) Recovery process, which may be useful to monitor the status of a coordinator recovery after a crash.
The new gp_autotstats_lock_wait server configuration parameter allows you to control whether ANALYZE commands triggered by automatic statistics collection will block if they cannot acquire the table lock.
The new optimizer_enable_right_outer_join server configuration parameter allows you to control whether GPORCA generates right outer joins. In situations in which you are observing poor performance related to right outer joins you may choose to suppress their use.
VMware Greenplum 7.1 now supports the VMware Greenplum Virtual Appliance. The virtual machine appliance contains everything you may need for an easy deploying of VMware Greenplum on vSphere. See VMware Greenplum on vSphere for more details.
The PostgresML extension now includes the pgml.train and pgml.predict functions for supervised learning.
You may configure one or more hosts outside your Greenplum cluster to use as a remote container host for your PL/Container workload, reducing the computing overload of the Greenplum hosts. See Configuring a Remote PL/Container for more details.
You can now use resource groups to manage and limit the total CPU resources for a PL/Container runtime. See PL/Container Resource Management for more details.
You can now download a VMware Greenplum 7 PL/Container image for R from VMware Tanzu Network.
The VACUUM command now includes the SKIP_DATABASE_STATS and ONLY_DATABASE_STATS clauses.
The output of the pg_config command now includes the Greenplum version.