合 GreenPlum 7.1.0新特性介绍

发布日期 2024年2月18日 · 已更新 2024年10月30日

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Tags： GreenPlum 新特性 GPDB 7

👉 本文共约5966个字，系统预计阅读时间或需23分钟。

简介
GreenPlum 7.1.0环境准备
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
新增pg_buffercache和gp_buffercache视图
孤儿文件相关
分区表相关
pg_filedump程序
故障恢复gprecoverseg
EXPLAIN ANALYZE增强
gppkg增强
系统视图gp_stat_progress_dtx_recovery
log_directory配置日志位置
新增optimizer_enable_right_outer_join服务器配置参数
VACUUM命令现在包含了SKIP_DATABASE_STATS和ONLY_DATABASE_STATS子句
pg_config命令的输出现在包括了Greenplum版本信息。
全部新特性原文
Release 7.1.0
New and Changed Features
参考

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

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
`crosstab`N`(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`crosstab`N``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=#

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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=# 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(# );

-------+---------------------+-------------+-------------+---------------------+--------

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.dbaup.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=#

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[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;

---------------+----------+-------------+---------------+-------------+---------------+----------------+---------+------------+------------------

-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

-------

(1 row)

db1=# select * from gp_buffercache_summary;

---------------+--------------+----------------+---------------+----------------+--------------------

-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。

select * from gp_toolkit.gp_check_orphaned_files;
select * from gp_toolkit.gp_check_missing_files;
select * from gp_toolkit.gp_check_missing_files_ext;

SELECT * FROM gp_toolkit.gp_move_orphaned_files('/home/gpadmin/orphaned');

select * from gp_toolkit.gp_check_orphaned_files;

select * from gp_toolkit.gp_check_missing_files;

select * from gp_toolkit.gp_check_missing_files_ext;

SELECT * FROM gp_toolkit.gp_move_orphaned_files('/home/gpadmin/orphaned');

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

[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

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)

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]

[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=#

[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;

-------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------

(0 rows)

postgres=# select * from gp_stat_progress_dtx_recovery;

------------------------------------------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------

gathering in-doubt orphaned transactions | 0 | 0 | 0 | 0 | 0

(1 row)

postgres=# select * from gp_stat_progress_dtx_recovery;

-------+----------------------------+--------------------------------+-------------------+-------------------------+---------------------

(0 rows)

postgres=# select * from gp_segment_configuration ;

------+---------+------+----------------+------+--------+------+----------+---------+--------------------------------------------

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 ~]$

-- 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.dbaup.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 ~]$

[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

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

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标签： GreenPlum 新特性 GPDB 7

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合 GreenPlum 7.1.0新特性介绍

简介

GreenPlum 7.1.0环境准备

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

新增pg_buffercache和gp_buffercache视图

孤儿文件相关

分区表相关

pg_filedump程序

故障恢复gprecoverseg

EXPLAIN ANALYZE增强

gppkg增强

系统视图gp_stat_progress_dtx_recovery

log_directory配置日志位置

新增optimizer_enable_right_outer_join服务器配置参数

VACUUM命令现在包含了SKIP_DATABASE_STATS和ONLY_DATABASE_STATS子句

相关文章

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合 GreenPlum 7.1.0新特性介绍

简介

GreenPlum 7.1.0环境准备

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

新增pg_buffercache和gp_buffercache视图

孤儿文件相关

分区表相关

pg_filedump程序

故障恢复gprecoverseg

EXPLAIN ANALYZE增强

gppkg增强

系统视图gp_stat_progress_dtx_recovery

log_directory配置日志位置

新增optimizer_enable_right_outer_join服务器配置参数

VACUUM命令现在包含了SKIP_DATABASE_STATS和ONLY_DATABASE_STATS子句

相关文章

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