David Wayne Birdsall created TRAFODION-2655: -----------------------------------------------
Summary: MDAM plans on prefixes sometimes not chosen when they should be Key: TRAFODION-2655 URL: https://issues.apache.org/jira/browse/TRAFODION-2655 Project: Apache Trafodion Issue Type: Bug Components: sql-cmp Affects Versions: 2.2-incubating Environment: Large clusters Reporter: David Wayne Birdsall Assignee: David Wayne Birdsall Below are two scripts that reproduce the problems. In the first problem, a query using parameters does not get an MDAM plan, even though it would be beneficial to do so. If the parameters on column C2 are replaced with literals that are close enough together, we do get the desired MDAM plan. In the second problem, using a larger version of the same table, a query with equality predicates on the first and third key columns ("first" and "third" ignoring the SALT column) does not get an MDAM plan on the first key column but chooses a full table scan instead. These problems were noticed on a cluster; it's not practical to create tables of the necessary size on a workstation. The scripts below reproduce the problem by faking the Optimizer into thinking it is dealing with much larger tables. First script: ?section setup drop table if exists MDAM_Q1_TEST; create table MDAM_Q1_TEST ( c1 integer not null, -- will have uec 2 c2 integer not null, -- will have uec 1,000,000 c3 integer not null, -- will have uec 766 c4 integer not null, -- will have uec 46 c5 integer not null, -- will have uec don't care (but 1,000,000) primary key ( c1, c2, c3, c4 ) ) salt using 4 partitions; upsert using load into MDAM_Q1_TEST select mod(c0+c1+c2+c3+c4,2), c0 + 10*c1 + 100*c2 + 1000*c3 + 10000*c4 + 100000*c5, c3 + 10*c1 + 74*c5, c4 + 4*c5, c5 + 10*c4 + 100*c3 + 1000*c2 + 10000*c1 + 100000*c0 from (values(1)) t transpose 0,1,2,3,4,5,6,7,8,9 as c0 transpose 0,1,2,3,4,5,6,7,8,9 as c1 transpose 0,1,2,3,4,5,6,7,8,9 as c2 transpose 0,1,2,3,4,5,6,7,8,9 as c3 transpose 0,1,2,3,4,5,6,7,8,9 as c4 transpose 0,1,2,3,4,5,6,7,8,9 as c5; update statistics for table MDAM_Q1_TEST on every column; -- next fake out the statistics so the optimizer will think there -- are 265 million rows in the table update sb_histograms set rowcount = 265 * rowcount where table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q1_TEST'); update sb_histogram_intervals set interval_rowcount = 265 * interval_rowcount where table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q1_TEST'); showstats for table MDAM_Q1_TEST on existing columns; ?section query1 prepare xx from select * from MDAM_Q1_TEST where c1 = ? and c2 > ? and c2 <= ? and c3 = ? and c4 = ?; explain xx; -- the plan gets a full scan instead of MDAM Second script ?section setup drop table if exists MDAM_Q2_TEST; create table MDAM_Q2_TEST ( c1 integer not null, -- will have uec 100 c2 integer not null, -- will have uec 2,000,000 c3 integer not null, -- will have uec 9,100 c4 integer not null, -- will have uec 11,800 c5 integer not null, -- will have uec don't care primary key ( c1, c2, c3, c4 ) ) salt using 4 partitions; upsert using load into MDAM_Q2_TEST select c3 + 10*c4, c0 + 10*c1 + 100*c2 + 1000*c3 + 10000*c4 + 100000*c5 + 1000000*c6, c3 + 10*c1 + 100*c5 + 900*c4, c4 + 10*c5 + 100*c2 + 600*c1 + 600*c3, c5 + 10*c4 + 100*c3 + 1000*c2 + 10000*c1 + 100000*c0 + 7*c6 from (values(1)) t transpose 0,1,2,3,4,5,6,7,8,9 as c0 transpose 0,1,2,3,4,5,6,7,8,9 as c1 transpose 0,1,2,3,4,5,6,7,8,9 as c2 transpose 0,1,2,3,4,5,6,7,8,9 as c3 transpose 0,1,2,3,4,5,6,7,8,9 as c4 transpose 0,1,2,3,4,5,6,7,8,9 as c5 transpose 0,1 as c6; ?section setupstats update statistics for table MDAM_Q2_TEST on every column; -- next fake out the statistics so the optimizer will think there -- are 11 billion rows in the table update sb_histograms set rowcount = 5500 * rowcount where table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST'); update sb_histogram_intervals set interval_rowcount = 5500 * interval_rowcount where table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST'); -- finally fake out the UEC on C2 so optimizer will think -- the UEC is 5 billion instead of 2 million update sb_histograms set total_uec = 2500 * total_uec where table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST') and column_number = 1 and colcount = 1; update sb_histogram_intervals i set interval_uec = 2500 * interval_uec where i.table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST') and i.histogram_id = (select histogram_id from sb_histograms h where h.table_uid = i.table_uid and h.column_number = 1 and h.colcount = 1); -- update the UECs in the multi-column histograms that include C2 update sb_histograms set total_uec = 5000000000 where total_uec = 2000000 and table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST'); update sb_histogram_intervals set interval_uec = 5000000000 where interval_uec = 2000000 and table_uid = (select object_uid from "_MD_".objects where object_name = 'MDAM_Q2_TEST'); showstats for table MDAM_Q2_TEST on existing columns; ?section query2 prepare xx from select * from MDAM_Q2_TEST where c1 = 23 and c3 = 497; explain xx; -- the plan does not get MDAM; but MDAM on C1 would be a good plan ?section query2x prepare yy from select * from MDAM_Q2_TEST where c1 = 23; explain yy; -- here we do get an MDAM plan on C1 -- This message was sent by Atlassian JIRA (v6.4.14#64029)