Greenplum merge insert 用法与性能 (insert on conflict)

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摘要： 标签 PostgreSQL , Greenplum , merge insert , insert on conflict , 合并插入 , 有则更新 , 无则插入 背景 PostgreSQL insert on conflict语法非常强大，支持合并写入（当违反某唯一约束时，冲突则更新，不冲突则写入），同时支持流式计算。

标签

PostgreSQL , Greenplum , merge insert , insert on conflict , 合并插入 , 有则更新 , 无则插入

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背景

PostgreSQL insert on conflict语法非常强大，支持合并写入（当违反某唯一约束时，冲突则更新，不冲突则写入），同时支持流式计算。

流计算例子链接：

《PostgreSQL 流式统计 - insert on conflict 实现 流式 UV(distinct), min, max, avg, sum, count ...》

《HTAP数据库 PostgreSQL 场景与性能测试之 22 - (OLTP) merge insert|upsert|insert on conflict|合并写入》

《PostgreSQL upsert功能(insert on conflict do)的用法》

《PostgreSQL 10.0 preview 功能增强 - 支持分区表ON CONFLICT .. DO NOTHING》

PostgreSQL insert on conflict语法如下：

Command:     INSERT    Description: create new rows in a table    Syntax:    [ WITH [ RECURSIVE ] with_query [, ...] ]    INSERT INTO table_name [ AS alias ] [ ( column_name [, ...] ) ]        [ OVERRIDING { SYSTEM | USER} VALUE ]        { DEFAULT VALUES | VALUES ( { expression | DEFAULT } [, ...] ) [, ...] | query }        [ ON CONFLICT [ conflict_target ] conflict_action ]        [ RETURNING * | output_expression [ [ AS ] output_name ] [, ...] ]        where conflict_target can be one of:            ( { index_column_name | ( index_expression ) } [ COLLATE collation ] [ opclass ] [, ...] ) [ WHERE index_predicate ]        ON CONSTRAINT constraint_name        and conflict_action is one of:            DO NOTHING        DO UPDATE SET { column_name = { expression | DEFAULT } |                        ( column_name [, ...] ) = [ ROW ] ( { expression | DEFAULT } [, ...] ) |                        ( column_name [, ...] ) = ( sub-SELECT )                      } [, ...]                  [ WHERE condition ]    

Greenplum的版本较低，还不支持insert on conflict的语法。

如果需要在Greenplum中实现类似的功能该如何操作？

DEMO

ID为PK，以它为合并列，举例。

1、目标表，也就是需要合并写入的目标：

create table t( id int primary key, c1 int , c2 int, c3 int, c4 int, c5 int, crt_time timestamp);    

2、中间表，也就是用户只管插入的表：

create table t_tmp(like t);    

写入一些中间记录。

insert into t_tmp values(1,1,2,3,null,null,now());    insert into t_tmp values(1,1,2,4,null,null,now());    insert into t_tmp values(1,1,2,3,null,7,now());    insert into t_tmp values(1,1,null,3,5,6,now());    

postgres=# select * from t_tmp;     id | c1 | c2 | c3 | c4 | c5 |          crt_time              ----+----+----+----+----+----+----------------------------      1 |  1 |  2 |  3 |    |    | 2017-12-13 17:03:16.28482      1 |  1 |  2 |  4 |    |    | 2017-12-13 17:03:16.286302      1 |  1 |  2 |  3 |    |  7 | 2017-12-13 17:03:16.635121      1 |  1 |    |  3 |  5 |  6 | 2017-12-13 17:03:25.434191    (4 rows)    

3、窗口合并，按唯一值约束，仅提取一条（可能存在窗口内合并的需求，例如按时间取最新，比如以最后一条为准，又或者以有值，且最新的为准）。

以有值切最新为准例子：

select distinct on (id)       id,      first_value(c1) over (partition by id order by (case when c1 is null then null else crt_time end) desc nulls last) as c1,      first_value(c2) over (partition by id order by (case when c2 is null then null else crt_time end) desc nulls last) as c2,      first_value(c3) over (partition by id order by (case when c3 is null then null else crt_time end) desc nulls last) as c3,      first_value(c4) over (partition by id order by (case when c4 is null then null else crt_time end) desc nulls last) as c4,      first_value(c5) over (partition by id order by (case when c5 is null then null else crt_time end) desc nulls last) as c5,      first_value(crt_time) over (partition by id order by crt_time desc) as crt_time      from t_tmp ;         id | c1 | c2 | c3 | c4 | c5 |          crt_time              ----+----+----+----+----+----+----------------------------      1 |  1 |  2 |  3 |  5 |  6 | 2017-12-13 17:03:25.434191    (1 row)    

存储中间结果：

create table t_tmp1 (like t) ;        insert into t_tmp1     select distinct on (id)       id,      first_value(c1) over (partition by id order by (case when c1 is null then null else crt_time end) desc nulls last) as c1,      first_value(c2) over (partition by id order by (case when c2 is null then null else crt_time end) desc nulls last) as c2,      first_value(c3) over (partition by id order by (case when c3 is null then null else crt_time end) desc nulls last) as c3,      first_value(c4) over (partition by id order by (case when c4 is null then null else crt_time end) desc nulls last) as c4,      first_value(c5) over (partition by id order by (case when c5 is null then null else crt_time end) desc nulls last) as c5,      first_value(crt_time) over (partition by id order by crt_time desc) as crt_time      from t_tmp ;    

4、合并写入：

将窗口提取的结果，合并写入目标表。

4.1、INNER JOIN，覆盖旧记录，同时补齐旧的字段（以NULL为判断条件。如果新的记录没有值，则取旧记录的值。）提取。

create table t_tmp2 (like t);        insert into t_tmp2    select     t_tmp.id,     coalesce(t_tmp.c1, t.c1),     coalesce(t_tmp.c2, t.c2),     coalesce(t_tmp.c3, t.c3),     coalesce(t_tmp.c4, t.c4),     coalesce(t_tmp.c5, t.c5),     coalesce(t_tmp.crt_time, t.crt_time)     from    t_tmp1 as t_tmp    inner join     t    using (id);    

4.2、DELETE USING，删除全量表的符合条件的记录。

delete from t using t_tmp2 where t.id=t_tmp2.id;    

4.3、INSERT

insert into t    select t_tmp1.* from t_tmp1 left join t_tmp2 using (id) where t_tmp2.* is null    union all    select * from t_tmp2;    

Greenplum merge insert 性能

硬件：使用一台64线程机器，单机启动48个segment。

1、全量数据20亿。

create table t(id int, c1 int , c2 int, c3 int, c4 int, c5 int, crt_time timestamp) with (APPENDONLY=true, ORIENTATION=column);        insert into t select id, null,null,null,null,10000, now() from generate_series(1,2000000000) t(id);    

2、增量数据1000万条，涉及500万个ID。

create table t_tmp(like t);        insert into t_tmp select random()*1000000, random()*100,null,null,null,null, clock_timestamp() from generate_series(1,2000000) t(id);    insert into t_tmp select random()*2000000, null,random()*100,null,null,null, clock_timestamp() from generate_series(1,2000000) t(id);    insert into t_tmp select random()*3000000, null,null,random()*100,null,null, clock_timestamp() from generate_series(1,2000000) t(id);    insert into t_tmp select random()*4000000, null,null,null,random()*100,null, clock_timestamp() from generate_series(1,2000000) t(id);    insert into t_tmp select random()*5000000, null,null,null,null,random()*100, clock_timestamp() from generate_series(1,2000000) t(id);        总耗时4.5秒。    

3、合并。

增量数据，窗口合并去重。

create table t_tmp1 (like t) ;        insert into t_tmp1     select distinct on (id)       id,      first_value(c1) over (partition by id order by ((case when c1 is null then null else crt_time end) is null), (case when c1 is null then null else crt_time end) desc) as c1,      first_value(c2) over (partition by id order by ((case when c2 is null then null else crt_time end) is null), (case when c2 is null then null else crt_time end) desc) as c2,      first_value(c3) over (partition by id order by ((case when c3 is null then null else crt_time end) is null), (case when c3 is null then null else crt_time end) desc) as c3,      first_value(c4) over (partition by id order by ((case when c4 is null then null else crt_time end) is null), (case when c4 is null then null else crt_time end) desc) as c4,      first_value(c5) over (partition by id order by ((case when c5 is null then null else crt_time end) is null), (case when c5 is null then null else crt_time end) desc) as c5,      first_value(crt_time) over (partition by id order by crt_time desc) as crt_time      from t_tmp ;        INSERT 0 3628283    Time: 5208.968 ms    

使用增量数据，提取并合并旧数据。

create table t_tmp2 (like t);        insert into t_tmp2    select     t_tmp.id,     coalesce(t_tmp.c1, t.c1),     coalesce(t_tmp.c2, t.c2),     coalesce(t_tmp.c3, t.c3),     coalesce(t_tmp.c4, t.c4),     coalesce(t_tmp.c5, t.c5),     coalesce(t_tmp.crt_time, t.crt_time)     from    t_tmp1 as t_tmp    inner join     t    using (id);        INSERT 0 3628282    Time: 9504.092 ms    

删除旧数据。

delete from t using t_tmp2 where t.id=t_tmp2.id;        DELETE 3628282    Time: 15356.920 ms    

插入新增、以及合并的增量数据。

insert into t    select t_tmp1.* from t_tmp1 left join t_tmp2 using (id) where t_tmp2.* is null    union all    select * from t_tmp2;        INSERT 0 3628283    Time: 778.014 ms    

数据校验

-- 中间结果        postgres=# select * from t_tmp where id=9;     id | c1 | c2 | c3 | c4 | c5 |          crt_time              ----+----+----+----+----+----+----------------------------      9 | 99 |    |    |    |    | 2017-12-13 23:18:14.65243      9 |  7 |    |    |    |    | 2017-12-13 23:18:14.817107      9 |    |  9 |    |    |    | 2017-12-13 23:18:15.292311      9 |    | 56 |    |    |    | 2017-12-13 23:18:15.449415    (4 rows)        -- 中间结果        postgres=# select * from t_tmp where id=446;     id  | c1 | c2 | c3 | c4 | c5 |          crt_time              -----+----+----+----+----+----+----------------------------     446 | 43 |    |    |    |    | 2017-12-13 23:18:14.291335     446 | 16 |    |    |    |    | 2017-12-13 23:18:14.715026     446 | 45 |    |    |    |    | 2017-12-13 23:18:15.048879     446 |    | 34 |    |    |    | 2017-12-13 23:18:15.646904     446 |    |  7 |    |    |    | 2017-12-13 23:18:15.81838     446 |    |    | 12 |    |    | 2017-12-13 23:18:16.220083     446 |    |    | 22 |    |    | 2017-12-13 23:18:16.26496     446 |    |    |    | 97 |    | 2017-12-13 23:18:17.464355     446 |    |    |    |    | 56 | 2017-12-13 23:18:18.427068    (9 rows)        -- 使用窗口合并后结果        postgres=# select * from t_tmp1 limit 10;     id  | c1 | c2 | c3 | c4 | c5 |          crt_time              -----+----+----+----+----+----+----------------------------       9 |  7 | 56 |    |    |    | 2017-12-13 23:18:15.449415  -- 验证      25 | 69 |    |  1 |    |    | 2017-12-13 23:18:16.161339     169 | 74 | 33 |  3 |    |    | 2017-12-13 23:18:16.71554     185 | 22 |    |    |    |    | 2017-12-13 23:18:14.93206     217 | 11 | 20 | 26 |    | 59 | 2017-12-13 23:18:17.911174     270 | 55 |    | 42 |    |    | 2017-12-13 23:18:16.494782     286 | 65 | 77 | 17 |    | 75 | 2017-12-13 23:18:17.895121     430 | 12 |    | 56 |    |    | 2017-12-13 23:18:16.744847     446 | 45 |  7 | 22 | 97 | 56 | 2017-12-13 23:18:18.427068  -- 验证     478 | 23 | 56 |    | 25 | 77 | 2017-12-13 23:18:18.293153    (10 rows)        -- 合并到全量表后结果        postgres=# select * from t where id=9;     id | c1 | c2 | c3 | c4 |  c5   |          crt_time              ----+----+----+----+----+-------+----------------------------      9 |  7 | 56 |    |    | 10000 | 2017-12-13 23:18:15.449415    (1 row)        postgres=# select * from t where id=446;     id  | c1 | c2 | c3 | c4 | c5 |          crt_time              -----+----+----+----+----+----+----------------------------     446 | 45 |  7 | 22 | 97 | 56 | 2017-12-13 23:18:18.427068    (1 row)    

4、合并总耗时：

35秒

5、耗时分布

增量数据1000万条，涉及500万个ID。

4.5秒

增量数据，窗口合并去重。

5.2秒

使用增量数据，提取并合并旧数据。

9.5秒

删除旧数据。

15秒

插入新增、以及合并的增量数据。

0.7秒

Greenplum merge insert 限制

比较复杂、而且不支持新值使用NULL值(要支持的话，得修改一下覆盖逻辑)。

参考

《Greenplum 排序nulls first|last的 SQL写法实现》

《PostgreSQL 流式统计 - insert on conflict 实现 流式 UV(distinct), min, max, avg, sum, count ...》

《HTAP数据库 PostgreSQL 场景与性能测试之 22 - (OLTP) merge insert|upsert|insert on conflict|合并写入》

《PostgreSQL upsert功能(insert on conflict do)的用法》

《PostgreSQL 10.0 preview 功能增强 - 支持分区表ON CONFLICT .. DO NOTHING》