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Comment: explain "+" and "-" in sort order (thanks Xiaoyong Zhu & Prasanth Jayachandran in user@hive.a.o)

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  • The plans of each Stage

    Code Block
    STAGE PLANS:
  Stage: Stage-1
    Map Reduce
      Alias -> Map Operator Tree:
        src
            Reduce Output Operator
              key expressions:
                    expr: key
                    type: string
              sort order: +
              Map-reduce partition columns:
                    expr: rand()
                    type: double
              tag: -1
              value expressions:
                    expr: substr(value, 4)
                    type: string
      Reduce Operator Tree:
        Group By Operator
          aggregations:
                expr: sum(UDFToDouble(VALUE.0))
          keys:
                expr: KEY.0
                type: string
          mode: partial1
          File Output Operator
            compressed: false
            table:
                input format: org.apache.hadoop.mapred.SequenceFileInputFormat
                output format: org.apache.hadoop.mapred.SequenceFileOutputFormat
                name: binary_table

  Stage: Stage-2
    Map Reduce
      Alias -> Map Operator Tree:
        /tmp/hive-zshao/67494501/106593589.10001
          Reduce Output Operator
            key expressions:
                  expr: 0
                  type: string
            sort order: +
            Map-reduce partition columns:
                  expr: 0
                  type: string
            tag: -1
            value expressions:
                  expr: 1
                  type: double
      Reduce Operator Tree:
        Group By Operator
          aggregations:
                expr: sum(VALUE.0)
          keys:
                expr: KEY.0
                type: string
          mode: final
          Select Operator
            expressions:
                  expr: 0
                  type: string
                  expr: 1
                  type: double
            Select Operator
              expressions:
                    expr: UDFToInteger(0)
                    type: int
                    expr: 1
                    type: double
              File Output Operator
                compressed: false
                table:
                    input format: org.apache.hadoop.mapred.TextInputFormat
                    output format: org.apache.hadoop.hive.ql.io.IgnoreKeyTextOutputFormat
                    serde: org.apache.hadoop.hive.serde2.dynamic_type.DynamicSerDe
                    name: dest_g1

  Stage: Stage-0
    Move Operator
      tables:
            replace: true
            table:
                input format: org.apache.hadoop.mapred.TextInputFormat
                output format: org.apache.hadoop.hive.ql.io.IgnoreKeyTextOutputFormat
                serde: org.apache.hadoop.hive.serde2.dynamic_type.DynamicSerDe
                name: dest_g1

    In this example there are 2 map/reduce stages (Stage-1 and Stage-2) and 1 File System related stage (Stage-0). Stage-0 basically moves the results from a temporary directory to the directory corresponding to the table dest_g1.
    Sort order indicates the number of columns in key expressions that are used for sorting. Each "+" represents one column sorted in ascending order, and each "-" represents a column sorted in descending order.

A map/reduce stage itself comprises of has 2 parts:

  • A mapping from table alias to Map Operator Tree -- This mapping tells the mappers which operator tree to call in order to process the rows from a particular table or result of a previous map/reduce stage. In Stage-1 in the above example, the rows from src table are processed by the operator tree rooted at a Reduce Output Operator. Similarly, in Stage-2 the rows of the results of Stage-1 are processed by another operator tree rooted at another Reduce Output Operator. Each of these Reduce Output Operators partitions the data to the reducers according to the criteria shown in the metadata.
  • A Reduce Operator Tree -- This is the operator tree which processes all the rows on the reducer of the map/reduce job. In Stage-1 for example, the Reducer Operator Tree is carrying out a partial aggregation where as the Reducer Operator Tree in Stage-2 computes the final aggregation from the partial aggregates computed in Stage-1

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