Greenplum创建表--分布键-php手册-php.cn

Greenplum创建表--分布键

Greenplum创建表--分布键

Greenplum是分布式系统，创建表时需要指定分布键（创建表需要CREATEDBA权限），目的在于将数据平均分布到各个segment。选择分布键非常重要，选择错了会导致数据不唯一，更严重的是会造成SQL性能急剧下降。
Greenplum有两种分布策略： 1、hash分布。
Greenplum默认使用hash分布策略。该策略可选一个或者多个列作为分布键（distribution key，简称DK）。分布键做hash算法来确认数据存放到对应的segment上。相同分布键值会hash到相同的segment上。表上最好有唯一键或者主键，这样能保证数据均衡分不到各个segment上。语法，distributed by。如果没有主键或者唯一键，默认选择第一列作为分布键。增加主键

2、随机（randomly）分布。数据会被随机分不到segment上，相同记录可能会存放在不同的segment上。随机分布可以保证数据平均，但是Greenplum没有跨节点的唯一键约束数据，所以无法保证数据唯一。基于唯一性和性能考虑，推荐使用hash分布，性能部分会另开一篇文档详细介绍。语法，distributed randomly。

一、hash分布键创建表，未指定分布列、分布类型，默认创建hash分布表，把第一列ID字段作为了分布键。

testDB=# create table t_hash(id int,name varchar(50)) distributed by (id);

CREATE TABLE

testDB=#

testDB=# \d t_hash

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) |

Distributed by: (id)

添加主键后，主键升级为分布键替代了id列。

testDB=# alter table t_hash addprimary key (name);

NOTICE: updating distribution policy to match new primary key

NOTICE: ALTER TABLE / ADD PRIMARY KEY will create implicit index "t_hash_pkey" for table "t_hash"

ALTER TABLE

testDB=# \d t_hash

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Indexes:

"t_hash_pkey" PRIMARY KEY, btree (name)

Distributed by: (name)

验证hash分布表可实现主键或者唯一键值的唯一性

testDB=# insert into t_hash values(1,'szlsd1');

INSERT 0 1

testDB=#

testDB=# insert into t_hash values(2,'szlsd1');

ERROR: duplicate key violates unique constraint "t_hash_pkey"(seg2 gp-s3:40000 pid=3855)

另外，主键列上依然能够创建唯一键

testDB=# create unique index u_id on t_hash(name);

CREATE INDEX

testDB=#

testDB=# \d t_hash

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Indexes:

"t_hash_pkey" PRIMARY KEY, btree (name)

"u_id" UNIQUE, btree (name)

Distributed by: (name)

但是，非主键列无法单独创建唯一索引，想创建的话必须包含多有分布键列

testDB=# create unique index uk_id on t_hash(id);

ERROR: UNIQUE indexmust contain all columns in the distribution keyof relation "t_hash"

testDB=# create unique index uk_id on t_hash(id,name);

CREATE INDEX

testDB=# \d t_hash

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Indexes:

"t_hash_pkey" PRIMARY KEY, btree (name)

"uk_id" UNIQUE, btree (id, name)

Distributed by: (name)

删除主键后，原hash分布键依然不变。

testDB=# alter table t_hash drop constraint t_hash_pkey;

ALTER TABLE

testDB=# \d t_hash

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Distributed by: (name)

当分布键不是主键或者唯一键时，我们来验证分布键的相同值落在一个segment的结论。下面的实验，name列是分布键，我们插入相同的name值，可以看到7条记录都落在了2号segment节点中。

testDB=#insert into t_hash values(1,'szlsd');

INSERT 0 1

testDB=#insert into t_hash values(2,'szlsd');

INSERT 0 1

testDB=#insert into t_hash values(3,'szlsd');

INSERT 0 1

testDB=#insert into t_hash values(4,'szlsd');

INSERT 0 1

testDB=#insert into t_hash values(5,'szlsd');

INSERT 0 1

testDB=#insert into t_hash values(6,'szlsd');

INSERT 0 1

testDB=#

testDB=# select gp_segment_id,count(*) from t_hash group by gp_segment_id;

gp_segment_id | count

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

2 |7

(1 row)

二、随机分布键创建随机分布表需加distributed randomly关键字，具体使用哪列作为分布键不得而知。

testDB=# create table t_random(id int ,name varchar(100))distributed randomly;

CREATE TABLE

testDB=#

testDB=# \d t_random

Table "public.t_random"

Column | Type | Modifiers

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

id | integer |

name | character varying(100) |

Distributed randomly

验证主键/唯一键的唯一性，可以看到随机分布表不能创建主键和唯一键

testDB=# alter table t_random add primary key (id,name);

ERROR: PRIMARY KEY and DISTRIBUTED RANDOMLY are incompatible

testDB=#

testDB=# create unique index uk_r_id on t_random(id);

ERROR: UNIQUE and DISTRIBUTED RANDOMLY are incompatible

testDB=#

从实验中可以看出无法实现数据的唯一性。并且，数据插入随机分布表，并不是轮询插入，实验中共有3个segment，但是在1号插入3条记录，在2号segment节点插入2条记录后，才在0号segment中插入数据。随机分布表如何实现数据平均分配不得而知。这个实验也验证了随机分布表的相同值分布在不同segment的结论。

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

1 | 1

(1 row)

testDB=#

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

2 | 1

1 | 1

(2 rows)

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

2 | 1

1 | 2

(2 rows)

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

2 | 2

1 | 2

(2 rows)

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

2 | 2

1 | 3

(2 rows)

testDB=# insert into t_random values(1,'szlsd3');

INSERT 0 1

testDB=# select gp_segment_id,count(*) from t_random group by gp_segment_id;

gp_segment_id | count

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

2 |2

1 |3

0 | 1

(3 rows)

三、CTAS继承原表分布键 Greenplum中有两种CTAS语法，无论哪种语法，都默认继承原表的分布键。但是，不会继承表的一些特殊属性，如主键、唯一键、APPENDONLY、COMPRESSTYPE（压缩）等。

testDB=# \d t_hash;

Table "public.t_hash"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Indexes:

"t_hash_pkey" PRIMARY KEY, btree (name)

"uk_id" UNIQUE, btree (id, name)

Distributed by: (name)

testDB=#

testDB=# create table t_hash_1 as select * from t_hash;

NOTICE: Table doesn't have 'DISTRIBUTED BY' clause -- Using column(s) named 'name' 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.

SELECT 0

testDB=# \d t_hash_1

Table "public.t_hash_1"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) |

Distributed by: (name)

testDB=#

testDB=# create table t_hash_2 (like t_hash);

NOTICE: Table doesn't have 'distributed by' clause, defaulting to distribution columns from LIKE table

CREATE TABLE

testDB=# \d t_hash_2

Table "public.t_hash_2"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Distributed by: (name)

如果CTAS创建表改变分布键，加上distributed by即可。

testDB=# create table t_hash_3 as select * from t_hash distributed by (id);

SELECT 0

testDB=#

testDB=# \d t_hash_3

Table "public.t_hash_3"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) |

Distributed by: (id)

testDB=#

testDB=# create table t_hash_4 (like t_hash) distributed by (id);

CREATE TABLE

testDB=#

testDB=# \d t_hash4

Did not find any relation named "t_hash4".

testDB=# \d t_hash_4

Table "public.t_hash_4"

Column | Type | Modifiers

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

id | integer |

name | character varying(50) | not null

Distributed by: (id)

CTAS时，randomly随机分布键要特别注意，一定要加上distributed randomly，不然原表是hash分布键，CTAS新表则是随机分布键。

testDB=# \d t_random

Table "public.t_random"

Column | Type | Modifiers

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

id | integer |

name | character varying(100) |

Distributed randomly

testDB=#

testDB=# \d t_random_1

Table "public.t_random_1"

Column | Type | Modifiers

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

id | integer |

name | character varying(100) |

Distributed by: (id)

testDB=# create table t_random_2 as select * from t_randomdistributed randomly;

SELECT 7

testDB=#

testDB=# \d t_random_2

Table "public.t_random_2"

Column |Type| Modifiers

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

id| integer|

name| character varying(100) |

Distributed randomly

参考：《Greenplum企业应用实战》《Greenplum4.2.2管理员指南》

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