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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (DRILL-4363) Apply row count based pruning for parquet table in LIMIT n query
Date Wed, 10 Feb 2016 14:43:18 GMT

    [ https://issues.apache.org/jira/browse/DRILL-4363?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15140894#comment-15140894
] 

ASF GitHub Bot commented on DRILL-4363:
---------------------------------------

Github user jacques-n commented on a diff in the pull request:

    https://github.com/apache/drill/pull/371#discussion_r52465362
  
    --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/planner/logical/DrillPushLimitToScanRule.java
---
    @@ -0,0 +1,107 @@
    +/**
    + * Licensed to the Apache Software Foundation (ASF) under one
    + * or more contributor license agreements.  See the NOTICE file
    + * distributed with this work for additional information
    + * regarding copyright ownership.  The ASF licenses this file
    + * to you under the Apache License, Version 2.0 (the
    + * "License"); you may not use this file except in compliance
    + * with the License.  You may obtain a copy of the License at
    + *
    + * http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.drill.exec.planner.logical;
    +
    +import com.google.common.collect.ImmutableList;
    +import org.apache.calcite.plan.RelOptRule;
    +import org.apache.calcite.plan.RelOptRuleCall;
    +import org.apache.calcite.plan.RelOptRuleOperand;
    +import org.apache.calcite.rel.RelNode;
    +import org.apache.calcite.util.Pair;
    +import org.apache.drill.exec.physical.base.GroupScan;
    +import org.apache.drill.exec.planner.logical.partition.PruneScanRule;
    +import org.apache.drill.exec.store.parquet.ParquetGroupScan;
    +
    +import java.io.IOException;
    +import java.util.concurrent.TimeUnit;
    +
    +public abstract class DrillPushLimitToScanRule extends RelOptRule {
    +  static final org.slf4j.Logger logger = org.slf4j.LoggerFactory.getLogger(DrillPushLimitToScanRule.class);
    +
    +  private DrillPushLimitToScanRule(RelOptRuleOperand operand, String description) {
    +    super(operand, description);
    +  }
    +
    +  public static DrillPushLimitToScanRule LIMIT_ON_SCAN = new DrillPushLimitToScanRule(
    +      RelOptHelper.some(DrillLimitRel.class, RelOptHelper.any(DrillScanRel.class)), "DrillPushLimitToScanRule_LimitOnScan")
{
    +    @Override
    +    public boolean matches(RelOptRuleCall call) {
    +      DrillScanRel scanRel = call.rel(1);
    +      return scanRel.getGroupScan() instanceof ParquetGroupScan; // It only applies to
Parquet.
    +    }
    +
    +    @Override
    +    public void onMatch(RelOptRuleCall call) {
    +        DrillLimitRel limitRel = call.rel(0);
    +        DrillScanRel scanRel = call.rel(1);
    +        doOnMatch(call, limitRel, scanRel, null);
    +    }
    +  };
    +
    +  public static DrillPushLimitToScanRule LIMIT_ON_PROJECT = new DrillPushLimitToScanRule(
    +      RelOptHelper.some(DrillLimitRel.class, RelOptHelper.some(DrillProjectRel.class,
RelOptHelper.any(DrillScanRel.class))), "DrillPushLimitToScanRule_LimitOnProject") {
    +    @Override
    +    public boolean matches(RelOptRuleCall call) {
    +      DrillScanRel scanRel = call.rel(2);
    +      return scanRel.getGroupScan() instanceof ParquetGroupScan; // It only applies to
Parquet.
    +    }
    +
    +    @Override
    +    public void onMatch(RelOptRuleCall call) {
    +      DrillLimitRel limitRel = call.rel(0);
    +      DrillProjectRel projectRel = call.rel(1);
    +      DrillScanRel scanRel = call.rel(2);
    +      doOnMatch(call, limitRel, scanRel, projectRel);
    +    }
    +  };
    +
    +
    +  protected void doOnMatch(RelOptRuleCall call, DrillLimitRel limitRel, DrillScanRel
scanRel, DrillProjectRel projectRel){
    +    try {
    +      final int rowCountRequested = (int) limitRel.getRows();
    +
    +      final Pair<GroupScan, Boolean>  newGroupScanPair = ParquetGroupScan.filterParquetScanByLimit((ParquetGroupScan)(scanRel.getGroupScan()),
rowCountRequested);
    --- End diff --
    
    How about:
    
    boolean applyLimit(int maxRecords)
    
    Returns whether the limit was applied. Default implementation in AbstractGroupScan is
return false.


> Apply row count based pruning for parquet table in LIMIT n query
> ----------------------------------------------------------------
>
>                 Key: DRILL-4363
>                 URL: https://issues.apache.org/jira/browse/DRILL-4363
>             Project: Apache Drill
>          Issue Type: Improvement
>            Reporter: Jinfeng Ni
>            Assignee: Aman Sinha
>             Fix For: 1.6.0
>
>
> In interactive data exploration use case, one common and probably first query that users
would use is " SELECT * from table LIMIT n", where n is a small number. Such query will give
user idea about the columns in the table.
> Normally, user would expect such query should be completed in very short time, since
it's just asking for small amount of rows, without any sort/aggregation.
> When table is small, there is no big problem for Drill. However, when the table is extremely
large,  Drill's response time is not as fast as what user would expect.
> In case of parquet table, it seems that query planner could do a bit better job : by
applying row count based pruning for such LIMIT n query.  The pruning is kind of similar to
what partition pruning will do, except that it uses row count, in stead of partition column
values. Since row count is available in parquet table, it's possible to do such pruning.
> The benefit of doing such pruning is clear: 1) for small "n",  such pruning would end
up with a few parquet files, in stead of thousands, or millions of files to scan. 2) execution
probably does not have to put scan into multiple minor fragments and start reading the files
concurrently, which will cause big IO overhead. 3) the physical plan itself is much smaller,
since it does not include the long list of parquet files, reduce rpc cost of sending the fragment
plans to multiple drillbits, and the overhead to serialize/deserialize the fragment plans.
>  
>  



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