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ASF GitHub Bot commented on DRILL-6118: --------------------------------------- Github user vvysotskyi commented on a diff in the pull request: https://github.com/apache/drill/pull/1104#discussion_r166310161 --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/physical/impl/project/ProjectRecordBatch.java --- @@ -596,10 +596,10 @@ private void classifyExpr(final NamedExpression ex, final RecordBatch incoming, final NameSegment ref = ex.getRef().getRootSegment(); final boolean exprHasPrefix = expr.getPath().contains(StarColumnHelper.PREFIX_DELIMITER); final boolean refHasPrefix = ref.getPath().contains(StarColumnHelper.PREFIX_DELIMITER); - final boolean exprIsStar = expr.getPath().equals(SchemaPath.WILDCARD); - final boolean refContainsStar = ref.getPath().contains(SchemaPath.WILDCARD); - final boolean exprContainsStar = expr.getPath().contains(SchemaPath.WILDCARD); - final boolean refEndsWithStar = ref.getPath().endsWith(SchemaPath.WILDCARD); + final boolean exprIsStar = expr.getPath().equals(SchemaPath.DYNAMIC_STAR); --- End diff -- This change became required after Calcite update. With the changes in CALCITE-1150, `*` is replaced by `**` after a query is parsed and `**` is added to the RowType. Therefore WILDCARD can't come from the plan and its usage should be replaced by `**`. > Handle item star columns during project / filter push down and directory > pruning > ---------------------------------------------------------------------------------- > > Key: DRILL-6118 > URL: https://issues.apache.org/jira/browse/DRILL-6118 > Project: Apache Drill > Issue Type: Improvement > Affects Versions: 1.12.0 > Reporter: Arina Ielchiieva > Assignee: Arina Ielchiieva > Priority: Major > Labels: doc-impacting > Fix For: 1.13.0 > > > Project push down, filter push down and partition pruning does not work with > dynamically expanded column with is represented as star in ITEM operator: > _ITEM($0, 'column_name')_ where $0 is a star. > This often occurs when view, sub-select or cte with star is issued. > To solve this issue we can create {{DrillFilterItemStarReWriterRule}} which > will rewrite such ITEM operator before filter push down and directory > pruning. For project into scan push down logic will be handled separately in > already existing rule {{DrillPushProjectIntoScanRule}}. Basically, we can > consider the following queries the same: > {{select col1 from t}} > {{select col1 from (select * from t)}} > *Use cases* > Since item star columns where not considered during project / filter push > down and directory pruning, push down and pruning did not happen. This was > causing Drill to read all columns from file (when only several are needed) or > ready all files instead. Views with star query is the most common example. > Such behavior significantly degrades performance for item star queries > comparing to queries without item star. > *EXAMPLES* > *Data set* > will create table with three files each in dedicated sub-folder: > {noformat} > use dfs.tmp; > create table `order_ctas/t1` as select cast(o_orderdate as date) as > o_orderdate from cp.`tpch/orders.parquet` where o_orderdate between date > '1992-01-01' and date '1992-01-03'; > create table `order_ctas/t2` as select cast(o_orderdate as date) as > o_orderdate from cp.`tpch/orders.parquet` where o_orderdate between date > '1992-01-04' and date '1992-01-06'; > create table `order_ctas/t3` as select cast(o_orderdate as date) as > o_orderdate from cp.`tpch/orders.parquet` where o_orderdate between date > '1992-01-07' and date '1992-01-09'; > {noformat} > *Filter push down* > {{select * from order_ctas where o_orderdate = date '1992-01-01'}} will read > only one file > {noformat} > 00-00 Screen > 00-01 Project(**=[$0]) > 00-02 Project(T1¦¦**=[$0]) > 00-03 SelectionVectorRemover > 00-04 Filter(condition=[=($1, 1992-01-01)]) > 00-05 Project(T1¦¦**=[$0], o_orderdate=[$1]) > 00-06 Scan(groupscan=[ParquetGroupScan > [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet]], > selectionRoot=/tmp/order_ctas, numFiles=1, numRowGroups=1, > usedMetadataFile=false, columns=[`**`]]]) > {noformat} > {{select * from (select * from order_ctas) where o_orderdate = date > '1992-01-01'}} will ready all three files > {noformat} > 00-00 Screen > 00-01 Project(**=[$0]) > 00-02 SelectionVectorRemover > 00-03 Filter(condition=[=(ITEM($0, 'o_orderdate'), 1992-01-01)]) > 00-04 Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath > [path=/tmp/order_ctas/t1/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t3/0_0_0.parquet]], selectionRoot=/tmp/order_ctas, > numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]]) > {noformat} > *Directory pruning* > {{select * from order_ctas where dir0 = 't1'}} will read data only from one > folder > {noformat} > 00-00 Screen > 00-01 Project(**=[$0]) > 00-02 Project(**=[$0]) > 00-03 Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath > [path=/tmp/order_ctas/t1/0_0_0.parquet]], selectionRoot=/tmporder_ctas, > numFiles=1, numRowGroups=1, usedMetadataFile=false, columns=[`**`]]]) > {noformat} > {{select * from (select * from order_ctas) where dir0 = 't1'}} will read > content of all three folders > {noformat} > 00-00 Screen > 00-01 Project(**=[$0]) > 00-02 SelectionVectorRemover > 00-03 Filter(condition=[=(ITEM($0, 'dir0'), 't1')]) > 00-04 Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath > [path=/tmp/order_ctas/t1/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t3/0_0_0.parquet]], selectionRoot=/tmp/order_ctas, > numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]]) > {noformat} > *Project into Scan push down* > {{select o_orderdate, count(1) from order_ctas group by o_orderdate}} will > ready only one column from the files > {noformat} > 00-00 Screen > 00-01 Project(o_orderdate=[$0], EXPR$1=[$1]) > 00-02 HashAgg(group=[{0}], EXPR$1=[COUNT()]) > 00-03 Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath > [path=/tmp/order_ctas/t1/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t3/0_0_0.parquet]], selectionRoot=/tmp/order_ctas, > numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`o_orderdate`]]]) > {noformat} > {{select o_orderdate, count(1) from (select * from order_ctas) group by > o_orderdate}} will ready all columns from the files > {noformat} > 00-00 Screen > 00-01 Project(col_vrchr=[$0], EXPR$1=[$1]) > 00-02 StreamAgg(group=[{0}], EXPR$1=[COUNT()]) > 00-03 Sort(sort0=[$0], dir0=[ASC]) > 00-04 Project(col_vrchr=[ITEM($0, 'o_orderdate')]) > 00-05 Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath > [path=/tmp/order_ctas/t1/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath > [path=/tmp/order_ctas/t3/0_0_0.parquet]], selectionRoot=/tmp/order_ctas, > numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]]) > {noformat} > This Jira aims to fix all three described cases above in order to improve > performance for queries with item star columns. > -- This message was sent by Atlassian JIRA (v7.6.3#76005)