检查数据倾斜分布 - 数据库编程

从传统数据库迁移到GP中一个重要的且经常被开发人员忽略的概念是数据分布，没有良好的设计表的分布键会导致严重的性能问题，以下函数将给开发人员及DBA检测一个表的数据倾斜情况。
-- Function: gpmg.data_skew(character varying)
 
-- DROP FUNCTION gpmg.data_skew(character varying);
 
CREATE OR REPLACE FUNCTION gpmg.data_skew(tablename character varying)
  RETURNS text AS
$BODY$
--2014-05-26,Gtlions,收集和统计数据倾斜情况
declare
  v_func character varying(200)='gpmg.data_skew()';
  v_begin_time timestamp;
  v_end_time timestamp;
  v_status int=0;
  v_msg text='Done.';
  v_record record;
 
  v_id integer;
  v_rq timestamp;  
  v_segs integer=64;
  v_totalnums bigint=0;
  v_maxskew numeric=0.0;
  v_minskew numeric=0.0;
  v_maxskew_seg varchar(20);
  v_minskew_seg varchar(20);
  v_maxrows bigint=0;
  v_minrows bigint=0;   
  v_result varchar(2000);
 
begin
  v_id=nextval('gpmg.commonseq');
  v_rq=now();
  v_begin_time=clock_timestamp();
  v_result = 'GP hava ';
  select into v_segs count(*) segs from gp_segment_configuration where role='p' and content<>-1;
  v_result = v_result||v_segs||' instances, Standard skew is '||1.0/v_segs||'. ';
  -- bg1 segid, bg2 节点记录数量
  execute 'insert into gpmg.commontab(seq,tabname,bg1,bg2) select '||v_id||','''||$1||''',gp_segment_id,count(*) segrownums from '||$1||' group by rollup(( gp_segment_id)) order by gp_segment_id';
  select into v_segs,v_totalnums v_segs,max(bg2) from gpmg.commontab where seq=v_id and tabname=$1;
  --nm1 标准倾斜率, nm2 节点倾斜率, nm3 标准-节点倾斜率绝对值
  update gpmg.commontab set nm1=1::numeric/v_segs,nm2=bg2::numeric/v_totalnums,nm3=abs(1::numeric/v_segs-bg2::numeric/v_totalnums) where seq=v_id and tabname=$1;
  select




 into v_maxskew,v_minskew max(nm2),min(nm2) from gpmg.commontab where seq=v_id and tabname=$1 and bg1 is not null;
 
  select into v_maxskew_seg hostname from gp_segment_configuration where role='p' and content in (select bg1 from gpmg.commontab where seq=v_id and tabname=$1 and bg1 is not null and nm2=v_maxskew limit 1);
  select into v_minskew_seg hostname from gp_segment_configuration where role='p' and content in (select bg1 from gpmg.commontab where seq=v_id and tabname=$1 and bg1 is not null and nm2=v_minskew limit 1);
 
  select into v_maxrows bg2 from gpmg.commontab where seq=v_id and tabname=$1 and bg1 is not null and nm2=v_maxskew limit 1;
  select into v_minrows bg2 from gpmg.commontab where seq=v_id and tabname=$1 and bg1 is not null and nm2=v_minskew limit 1;
 
  v_result =v_result ||'You Table ['||$1||'] skew info: [table_totalrows:'||v_totalnums||', maxskew:seg-'||v_maxskew_seg||', rows-'||v_maxrows||' '||v_maxskew||', minskew:seg-'||v_minskew_seg||', rows-'||v_minrows||' '||v_minskew||']';
  delete from gpmg.commontab where seq=v_id and tabname=$1;
  return v_result;
  v_end_time=clock_timestamp();
end;
$BODY$
  LANGUAGE plpgsql VOLATILE;
ALTER FUNCTION gpmg.data_skew(character varying)
  OWNER TO gpadmin;
GRANT EXECUTE ON FUNCTION gpmg.data_skew(character varying) TO public;
GRANT EXECUTE ON FUNCTION gpmg.data_skew(character varying) TO gpadmin;

bigdatagp=# select gpmg.data_skew('gpmg.manager_table');
                                                                                                            data_skew                                                  
                                                           
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
-----------------------------------------------------------
 GP hava 64 instances, Standard skew is 0.01562500000000000000. You Table [gpmg.
检查数据倾斜分布(一)
