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https://issues.apache.org/jira/browse/DRILL-6118?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Arina Ielchiieva updated DRILL-6118:
------------------------------------
Description:
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.
was:
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.
*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.
> 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.
>
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