[GitHub] carbondata pull request #1886: [CARBONDATA-2098]Add Documentation for Pre-Ag...

[qiuchenjian-2]

GitHub user sraghunandan opened a pull request:

    https://github.com/apache/carbondata/pull/1886

    [CARBONDATA-2098]Add Documentation for Pre-Aggregate tables

    Be sure to do all of the following checklist to help us incorporate
    your contribution quickly and easily:
   
     - [x] Any interfaces changed?
     No
     - [x] Any backward compatibility impacted?
     No
     - [x] Document update required?
    Updated documentation
     - [x] Testing done
            Please provide details on
            - Whether new unit test cases have been added or why no new tests are required?
            - How it is tested? Please attach test report.
            - Is it a performance related change? Please attach the performance test report.
            - Any additional information to help reviewers in testing this change.
           NA
     - [X] For large changes, please consider breaking it into sub-tasks under an umbrella JIRA.
    NA


You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/sraghunandan/carbondata-1 partition_preagg_documentation

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/carbondata/pull/1886.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #1886
   
----
commit 49ead42c07aae85afbaac74ba5fbbd256a98fd72
Author: Raghunandan S <carbondatacontributions@...>
Date:   2018-01-29T03:24:49Z

    Add Documentation for Pre-Aggregate tables

----


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[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Success with Spark 2.2.1, Please check CI http://88.99.58.216:8080/job/ApacheCarbonPRBuilder/2036/



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[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder1/3273/



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[qiuchenjian-2]

Github user ravipesala commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    SDV Build Fail , Please check CI http://144.76.159.231:8080/job/ApacheSDVTests/3227/



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[qiuchenjian-2]

Github user jackylk commented on a diff in the pull request:

    https://github.com/apache/carbondata/pull/1886#discussion_r165249189
 
    --- Diff: docs/data-management-on-carbondata.md ---
    @@ -703,6 +704,194 @@ This tutorial is going to introduce all commands and data operations on CarbonDa
       * The partitioned column can be excluded from SORT_COLUMNS, this will let other columns to do the efficient sorting.
       * When writing SQL on a partition table, try to use filters on the partition column.
     
    +## PRE-AGGREGATE TABLES
    --- End diff --
   
    Please add some example to show the plan matching mechanism, like what query will hit which datamap


---

[qiuchenjian-2]

Github user chenliang613 commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    @sraghunandan  please add pre-agg example, it is better to have the performance comparison inside example.


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[qiuchenjian-2]

Github user sraghunandan commented on a diff in the pull request:

    https://github.com/apache/carbondata/pull/1886#discussion_r165290684
 
    --- Diff: docs/data-management-on-carbondata.md ---
    @@ -703,6 +704,194 @@ This tutorial is going to introduce all commands and data operations on CarbonDa
       * The partitioned column can be excluded from SORT_COLUMNS, this will let other columns to do the efficient sorting.
       * When writing SQL on a partition table, try to use filters on the partition column.
     
    +## PRE-AGGREGATE TABLES
    --- End diff --
   
    added example


---

[qiuchenjian-2]

Github user sraghunandan commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    @jackylk @chenliang613 added examples. pls review


---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Failed with Spark 2.2.1, Please check CI http://88.99.58.216:8080/job/ApacheCarbonPRBuilder/2167/



---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Failed  with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder1/3406/



---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Failed with Spark 2.2.1, Please check CI http://88.99.58.216:8080/job/ApacheCarbonPRBuilder/2171/



---

[qiuchenjian-2]

Github user ravipesala commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    SDV Build Fail , Please check CI http://144.76.159.231:8080/job/ApacheSDVTests/3283/



---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Failed with Spark 2.2.1, Please check CI http://88.99.58.216:8080/job/ApacheCarbonPRBuilder/2201/



---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Failed  with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder1/3441/



---

[qiuchenjian-2]

Github user ravipesala commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    SDV Build Success , Please check CI http://144.76.159.231:8080/job/ApacheSDVTests/3305/



---

[qiuchenjian-2]

Github user kumarvishal09 commented on a diff in the pull request:

    https://github.com/apache/carbondata/pull/1886#discussion_r165641742
 
    --- Diff: docs/data-management-on-carbondata.md ---
    @@ -748,6 +749,250 @@ This tutorial is going to introduce all commands and data operations on CarbonDa
       * The partitioned column can be excluded from SORT_COLUMNS, this will let other columns to do the efficient sorting.
       * When writing SQL on a partition table, try to use filters on the partition column.
     
    +## PRE-AGGREGATE TABLES
    +  Carbondata supports pre aggregating of data so that OLAP kind of queries can fetch data
    +  much faster.Aggregate tables are created as datamaps so that the handling is as efficient as
    +  other indexing support.Users can create as many aggregate tables they require as datamaps to
    +  improve their query performance,provided the storage requirements and loading speeds are
    +  acceptable.
    +  
    +  For main table called **sales** which is defined as
    +  
    +  ```
    +  CREATE TABLE sales (
    +  order_time timestamp,
    +  user_id string,
    +  sex string,
    +  country string,
    +  quantity int,
    +  price bigint)
    +  STORED BY 'carbondata'
    +  ```
    +  
    +  user can create pre-aggregate tables using the DDL
    +  
    +  ```
    +  CREATE DATAMAP agg_sales
    +  ON TABLE sales
    +  USING "preaggregate"
    +  AS
    +  SELECT country, sex, sum(quantity), avg(price)
    +  FROM sales
    +  GROUP BY country, sex
    +  ```
    +  
    +<b><p align="left">Functions supported in pre-aggregate tables</p></b>
    +
    +| Function | Rollup supported |
    +|-----------|----------------|
    +| SUM | Yes |
    +| AVG | Yes |
    +| MAX | Yes |
    +| MIN | Yes |
    +| COUNT | Yes |
    +| DISTINCT COUNT | No |
    --- End diff --
   
    Currently we are not supporting distinct count and in future only for timeseries we can support


---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder1/3471/



---

[qiuchenjian-2]

Github user CarbonDataQA commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    Build Success with Spark 2.2.1, Please check CI http://88.99.58.216:8080/job/ApacheCarbonPRBuilder/2231/



---

[qiuchenjian-2]

Github user chenliang613 commented on the issue:

    https://github.com/apache/carbondata/pull/1886
 
    LGTM


---

[qiuchenjian-2]

Github user chenliang613 commented on a diff in the pull request:

    https://github.com/apache/carbondata/pull/1886#discussion_r165807899
 
    --- Diff: examples/spark2/src/main/scala/org/apache/carbondata/examples/TimeSeriesPreAggregateTableExample.scala ---
    @@ -0,0 +1,105 @@
    +/*
    + * 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.carbondata.examples
    +
    +import java.io.File
    +
    +import org.apache.spark.sql.SaveMode
    +
    +import org.apache.carbondata.core.constants.CarbonCommonConstants
    +import org.apache.carbondata.core.util.CarbonProperties
    +
    +/**
    + * This example is for time series pre-aggregate tables.
    + */
    +
    +object TimeSeriesPreAggregateTableExample {
    +
    +  def main(args: Array[String]) {
    +
    +    val rootPath = new File(this.getClass.getResource("/").getPath
    +                            + "../../../..").getCanonicalPath
    +    val testData = s"$rootPath/integration/spark-common-test/src/test/resources/timeseriestest.csv"
    +    val spark = ExampleUtils.createCarbonSession("TimeSeriesPreAggregateTableExample")
    +
    +    spark.sparkContext.setLogLevel("ERROR")
    +
    +    import spark.implicits._
    +
    +    import scala.util.Random
    +    val r = new Random()
    +    val df = spark.sparkContext.parallelize(1 to 10 * 1000 * 1000 )
    --- End diff --
   
    please reduce the data size


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