[jira] [Created] (CARBONDATA-1625) Introduce new datatype of varchar(size) to store column length more than short limit.

[Akash R Nilugal (Jira)]

Zhichao  Zhang created CARBONDATA-1625:
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             Summary: Introduce new datatype of  varchar(size) to store column length more than short limit.
                 Key: CARBONDATA-1625
                 URL: https://issues.apache.org/jira/browse/CARBONDATA-1625
             Project: CarbonData
          Issue Type: New Feature
          Components: file-format
            Reporter: Zhichao  Zhang
            Priority: Minor


I am using Spark 2.1 + CarbonData 1.2, and find that if
enable.unsafe.sort=true, the length of bytes of column exceed 32768, it will
load data unsuccessfully.

My test code:
    val longStr = sb.toString()  // the getBytes length of longStr exceeds 32768
    println(longStr.length())
    println(longStr.getBytes("UTF-8").length)
   
    import spark.implicits._
    val df1 = spark.sparkContext.parallelize(0 to 1000)
      .map(x => ("a", x.toString(), longStr, x, x.toLong, x * 2))
      .toDF("stringField1", "stringField2", "stringField3", "intField",
"longField", "int2Field")
     
    val df2 = spark.sparkContext.parallelize(1001 to 2000)
      .map(x => ("b", x.toString(), (x % 2).toString(), x, x.toLong, x * 2))
      .toDF("stringField1", "stringField2", "stringField3", "intField",
"longField", "int2Field")
     
    val df3 = df1.union(df2)
    val tableName = "study_carbondata_test"
    spark.sql(s"DROP TABLE IF EXISTS ${tableName} ").show()
    val sortScope = "LOCAL_SORT"   // LOCAL_SORT   GLOBAL_SORT
    spark.sql(s"""
        |  CREATE TABLE IF NOT EXISTS ${tableName} (
        |    stringField1          string,
        |    stringField2          string,
        |    stringField3          string,
        |    intField              int,
        |    longField             bigint,
        |    int2Field             int
        |  )
        |  STORED BY 'carbondata'
        |  TBLPROPERTIES('DICTIONARY_INCLUDE'='stringField1, stringField2',
        |    'SORT_COLUMNS'='stringField1, stringField2, intField,
longField',
        |    'SORT_SCOPE'='${sortScope}',
        |    'NO_INVERTED_INDEX'='stringField3, int2Field',
        |    'TABLE_BLOCKSIZE'='64'
        |  )
       """.stripMargin)
    df3.write
      .format("carbondata")  
      .option("tableName", "study_carbondata_test")
      .option("compress", "true")  // just valid when tempCSV is true
      .option("tempCSV", "false")
      .option("single_pass", "true")
      .mode(SaveMode.Append)
      .save()

The error message:
*java.lang.NegativeArraySizeException
        at
org.apache.carbondata.processing.newflow.sort.unsafe.UnsafeCarbonRowPage.getRow(UnsafeCarbonRowPage.java:182)
        at
org.apache.carbondata.processing.newflow.sort.unsafe.holder.UnsafeInmemoryHolder.readRow(UnsafeInmemoryHolder.java:63)
        at
org.apache.carbondata.processing.newflow.sort.unsafe.merger.UnsafeSingleThreadFinalSortFilesMerger.startSorting(UnsafeSingleThreadFinalSortFilesMerger.java:114)
        at
org.apache.carbondata.processing.newflow.sort.unsafe.merger.UnsafeSingleThreadFinalSortFilesMerger.startFinalMerge(UnsafeSingleThreadFinalSortFilesMerger.java:81)
        at
org.apache.carbondata.processing.newflow.sort.impl.UnsafeParallelReadMergeSorterImpl.sort(UnsafeParallelReadMergeSorterImpl.java:105)
        at
org.apache.carbondata.processing.newflow.steps.SortProcessorStepImpl.execute(SortProcessorStepImpl.java:62)
        at
org.apache.carbondata.processing.newflow.steps.DataWriterProcessorStepImpl.execute(DataWriterProcessorStepImpl.java:87)
        at
org.apache.carbondata.processing.newflow.DataLoadExecutor.execute(DataLoadExecutor.java:51)
        at
org.apache.carbondata.spark.rdd.NewDataFrameLoaderRDD$$anon$2.<init>(NewCarbonDataLoadRDD.scala:442)
        at
org.apache.carbondata.spark.rdd.NewDataFrameLoaderRDD.internalCompute(NewCarbonDataLoadRDD.scala:405)
        at
org.apache.carbondata.spark.rdd.CarbonRDD.compute(CarbonRDD.scala:62)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)*

Currently, the length of column was stored by short type.

Introduce new datatype of  varchar(size) to store column length more than short limit.



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