Hive 底层执行流程

栏目: 服务器 · 发布时间: 5年前

内容简介：Hive并不是简简单单写SQL，因为我们要进行层层调优，如果连Hive的内部运行机制都搞不清，那么hive对我们来说仅仅是一个黑箱，高效率的调优无从谈起，所以我们很有必要了解下Hive是如何将SQL转化为MapReduce任务的呢？我们以下面这个SQL为例整个编译过程分为六个阶段：

Hive并不是简简单单写SQL，因为我们要进行层层调优，如果连Hive的内部运行机制都搞不清，那么hive对我们来说仅仅是一个黑箱，高效率的调优无从谈起，所以我们很有必要了解下Hive是如何将 SQL 转化为MapReduce任务的呢？

Hive 底层执行流程

我们以下面这个SQL为例

FROM src INSERT OVERWRITE TABLE dest_g1 SELECT src.key, sum(substr(src.value,4)) GROUP BY src.key;

整个编译过程分为六个阶段：

1.Antlr定义SQL的语法规则，完成SQL词法，语法解析，将SQL

HiveLexerX ， HiveParser 分别是Antlr对SQL编译后自动生成的词法解析和语法解析类，在这两个类中进行复杂的解析。

例子中的AST tree为

ABSTRACT SYNTAX TREE:
(TOK_QUERY (TOK_FROM (TOK_TABREF src))
(TOK_INSERT (TOK_DESTINATION (TOK_TAB dest_g1)) 
(TOK_SELECT (TOK_SELEXPR (TOK_COLREF src key)) 
(TOK_SELEXPR (TOK_FUNCTION sum (TOK_FUNCTION substr (TOK_COLREF src value) 4))))
(TOK_GROUPBY (TOK_COLREF src key))))

2.遍历AST Tree，抽象出查询的基本组成单元QueryBlock

AST Tree 仍然非常复杂，不够结构化，不方便直接翻译为 MapReduce 程序， AST

Tree 转化为 QueryBlock (QB)就是将 SQL 进一部抽象和结构化。

AST Tree 生成 QueryBlock 的过程是一个递归的过程，先序遍历 AST Tree ，遇到不

同的Token 节点(理解为特殊标记)，保存到相应的属性中，主要包含以下几个过程

TOK_QUERY => 创建 QB 对象，循环递归子节点
TOK_FROM => 将表名语法部分保存到 QB 对象的 aliasToTabs 等属性中
TOK_INSERT => 循环递归子节点
TOK_DESTINATION => 将输出目标的语法部分保存在 QBParseInfo 对象的nameToDest 属性中
TOK_SELECT => 分别将查询表达式的语法部分保存在 destToSelExpr 、destToAggregationExprs 、 destToDistinctFuncExprs 三个属性中
TOK_WHERE => 将 Where 部分的语法保存在 QBParseInfo 对象的destToWhereExpr 属性中

3.遍历QueryBlock，翻译为执行操作树OperatorTree

Hive 最终生成的 MapReduce 任务， Map 阶段和 Reduce 阶段均由 Operator Tree

组成。逻辑操作符，就是在 Map 阶段或者 Reduce 阶段完成单一特定的操作。

基本的操作符包括

TableScanOperator、SelectOperator、FilterOperator、JoinOperator、GroupByOperator、ReduceSinkOperator

QueryBlock 生成 Operator Tree 就是遍历上一个过程中生成的 QB 和 QBParseInfo

对象的保存

语法的属性，包含如下几个步骤：

QB#aliasToSubq => 有子查询，递归调用
QB#aliasToTabs => TableScanOperator
QBParseInfo#joinExpr => QBJoinTree => ReduceSinkOperator + JoinOperator
QBParseInfo#destToWhereExpr => FilterOperator
QBParseInfo#destToGroupby => ReduceSinkOperator +GroupByOperator
QBParseInfo#destToOrderby => ReduceSinkOperator + ExtractOperator

由于 Join/GroupBy/OrderBy 均需要在 Reduce 阶段完成，所以在生成相应操作的Operator 之前都会先生成一个 ReduceSinkOperator ，将字段组合并序列化为 Reduce Key/value,Partition Key

SQL例子翻译成OperatorTree

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

4.Logical Optimizer进行OperatorTree变换，合并不必要的

使用 ReduceSinkOperator ，减少shuffle数据量。大部分逻辑层优化器通过变换 OperatorTree ，合并操作符，达到减少 MapReduce Job ，减少 shuffle 数据量的目的。

5.遍历OperatorTree，翻译为Task tree

OperatorTree 转化为 Task tree的过程分为下面几个阶段

对输出表生成 MoveTask
从 OperatorTree 的其中一个根节点向下深度优先遍历
ReduceSinkOperator 标示 Map/Reduce 的界限，多个 Job 间的界限
遍历其他根节点，遇过碰到 JoinOperator 合并 MapReduceTask
生成 StatTask 更新元数据
剪断 Map 与 Reduce 间的 Operator 的关系

6. PhysicalOptimizer 对Task tree优化，生成最终的执行计划

7、执行

以上就是HiveSQL的底层执行流程

打印SQL运行相关信息

我们在开发中，可以使用下面这个语句来打印SQL语句的相关运行信息

EXPLAIN [EXTENDED|DEPENDENCY|AUTHORIZATION] query

注:我的版本是 hive-1.1.0-cdh5.7.0 ，所以只可用三个可选属性，如果您版本比较高的话，可以去官网查阅对应属性

下面我对三种可选属性进行简单介绍

EXTENDED

EXTENDED：打印SQL解析成AST&Operator Tree最全面的信息

hive (g6_hadoop)> explain EXTENDED insert  OVERWRITE table g6_access_orc_explain select domain,count(1) num from g6_access_orc where traffic>'99900' group by domain;
OK
Explain
ABSTRACT SYNTAX TREE:

TOK_QUERY
   TOK_FROM
      TOK_TABREF
         TOK_TABNAME
            g6_access_orc
   TOK_INSERT
      TOK_DESTINATION
         TOK_TAB
            TOK_TABNAME
               g6_access_orc_explain
      TOK_SELECT
         TOK_SELEXPR
            TOK_TABLE_OR_COL
               domain
         TOK_SELEXPR
            TOK_FUNCTION
               count
               1
            num
      TOK_WHERE
         >
            TOK_TABLE_OR_COL
               traffic
            '99900'
      TOK_GROUPBY
         TOK_TABLE_OR_COL
            domain

STAGE DEPENDENCIES:
  Stage-1 is a root stage
  Stage-0 depends on stages: Stage-1
  Stage-2 depends on stages: Stage-0

STAGE PLANS:
  Stage: Stage-1
    Map Reduce
      Map Operator Tree:
          TableScan
            alias: g6_access_orc
            Statistics: Num rows: 260326 Data size: 188215698 Basic stats: COMPLETE Column stats: NONE
            GatherStats: false
            Filter Operator
              isSamplingPred: false
              predicate: (traffic > 99900) (type: boolean)
              Statistics: Num rows: 86775 Data size: 62738325 Basic stats: COMPLETE Column stats: NONE
              Select Operator
                expressions: domain (type: string)
                outputColumnNames: domain
                Statistics: Num rows: 86775 Data size: 62738325 Basic stats: COMPLETE Column stats: NONE
                Group By Operator
                  aggregations: count(1)
                  keys: domain (type: string)
                  mode: hash
                  outputColumnNames: _col0, _col1
                  Statistics: Num rows: 86775 Data size: 62738325 Basic stats: COMPLETE Column stats: NONE
                  Reduce Output Operator
                    key expressions: _col0 (type: string)
                    sort order: +
                    Map-reduce partition columns: _col0 (type: string)
                    Statistics: Num rows: 86775 Data size: 62738325 Basic stats: COMPLETE Column stats: NONE
                    tag: -1
                    value expressions: _col1 (type: bigint)
                    auto parallelism: false
      Path -> Alias:
        hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc [g6_access_orc]
      Path -> Partition:
        hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc 
          Partition
            base file name: g6_access_orc
            input format: org.apache.hadoop.hive.ql.io.orc.OrcInputFormat
            output format: org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat
            properties:
              COLUMN_STATS_ACCURATE true
              bucket_count -1
              columns cdn,region,level,time,ip,domain,url,traffic
              columns.comments 
              columns.types string:string:string:string:string:string:string:bigint
              field.delim   
              file.inputformat org.apache.hadoop.hive.ql.io.orc.OrcInputFormat
              file.outputformat org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat
              location hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc
              name g6_hadoop.g6_access_orc
              numFiles 1
              numRows 260326
              rawDataSize 188215698
              serialization.ddl struct g6_access_orc { string cdn, string region, string level, string time, string ip, string domain, string url, i64 traffic}
              serialization.format  
              serialization.lib org.apache.hadoop.hive.ql.io.orc.OrcSerde
              totalSize 8567798
              transient_lastDdlTime 1557676635
            serde: org.apache.hadoop.hive.ql.io.orc.OrcSerde

              input format: org.apache.hadoop.hive.ql.io.orc.OrcInputFormat
              output format: org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat
              properties:
                COLUMN_STATS_ACCURATE true
                bucket_count -1
                columns cdn,region,level,time,ip,domain,url,traffic
                columns.comments 
                columns.types string:string:string:string:string:string:string:bigint
                field.delim     
                file.inputformat org.apache.hadoop.hive.ql.io.orc.OrcInputFormat
                file.outputformat org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat
                location hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc
                name g6_hadoop.g6_access_orc
                numFiles 1
                numRows 260326
                rawDataSize 188215698
                serialization.ddl struct g6_access_orc { string cdn, string region, string level, string time, string ip, string domain, string url, i64 traffic}
                serialization.format    
                serialization.lib org.apache.hadoop.hive.ql.io.orc.OrcSerde
                totalSize 8567798
                transient_lastDdlTime 1557676635
              serde: org.apache.hadoop.hive.ql.io.orc.OrcSerde
              name: g6_hadoop.g6_access_orc
            name: g6_hadoop.g6_access_orc
      Truncated Path -> Alias:
        /g6_hadoop.db/g6_access_orc [g6_access_orc]
      Needs Tagging: false
      Reduce Operator Tree:
        Group By Operator
          aggregations: count(VALUE._col0)
          keys: KEY._col0 (type: string)
          mode: mergepartial
          outputColumnNames: _col0, _col1
          Statistics: Num rows: 43387 Data size: 31368801 Basic stats: COMPLETE Column stats: NONE
          File Output Operator
            compressed: false
            GlobalTableId: 1
            directory: hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain/.hive-staging_hive_2019-05-23_23-37-06_889_2210604962026719569-1/-ext-10000
            NumFilesPerFileSink: 1
            Statistics: Num rows: 43387 Data size: 31368801 Basic stats: COMPLETE Column stats: NONE
            Stats Publishing Key Prefix: hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain/.hive-staging_hive_2019-05-23_23-37-06_889_2210604962026719569-1/-ext-10000/
            table:
                input format: org.apache.hadoop.mapred.TextInputFormat
                output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
                properties:
                  COLUMN_STATS_ACCURATE true
                  bucket_count -1
                  columns domain,num
                  columns.comments 
                  columns.types string:bigint
                  field.delim |
                  file.inputformat org.apache.hadoop.mapred.TextInputFormat
                  file.outputformat org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
                  location hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain
                  name g6_hadoop.g6_access_orc_explain
                  numFiles 1
                  numRows 7
                  rawDataSize 149
                  serialization.ddl struct g6_access_orc_explain { string domain, i64 num}
                  serialization.format |
                  serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
                  totalSize 156
                  transient_lastDdlTime 1558661108
                serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
                name: g6_hadoop.g6_access_orc_explain
            TotalFiles: 1
            GatherStats: true
            MultiFileSpray: false

  Stage: Stage-0
    Move Operator
      tables:
          replace: true
          source: hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain/.hive-staging_hive_2019-05-23_23-37-06_889_2210604962026719569-1/-ext-10000
          table:
              input format: org.apache.hadoop.mapred.TextInputFormat
              output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
              properties:
                COLUMN_STATS_ACCURATE true
                bucket_count -1
                columns domain,num
                columns.comments 
                columns.types string:bigint
                field.delim |
                file.inputformat org.apache.hadoop.mapred.TextInputFormat
                file.outputformat org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
                location hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain
                name g6_hadoop.g6_access_orc_explain
                numFiles 1
                numRows 7
                rawDataSize 149
                serialization.ddl struct g6_access_orc_explain { string domain, i64 num}
                serialization.format |
                serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
                totalSize 156
                transient_lastDdlTime 1558661108
              serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
              name: g6_hadoop.g6_access_orc_explain

  Stage: Stage-2
    Stats-Aggr Operator
      Stats Aggregation Key Prefix: hdfs://ruozeclusterg6/user/hive/warehouse/g6_hadoop.db/g6_access_orc_explain/.hive-staging_hive_2019-05-23_23-37-06_889_2210604962026719569-1/-ext-10000/

Time taken: 1.359 seconds, Fetched: 198 row(s)

AUTHORIZATION

AUTHORIZATION :打印SQL运行相关权限

hive (g6_hadoop)> explain AUTHORIZATION insert  OVERWRITE table g6_access_orc_explain select domain,count(1) num from g6_access_orc where traffic>'99900' group by domain;
OK
Explain
INPUTS: 
  g6_hadoop@g6_access_orc
OUTPUTS: 
  g6_hadoop@g6_access_orc_explain
CURRENT_USER: 
  hadoop
OPERATION: 
  QUERY
AUTHORIZATION_FAILURES: 
  No privilege 'Update' found for outputs { database:g6_hadoop, table:g6_access_orc_explain}
  No privilege 'Select' found for inputs { database:g6_hadoop, table:g6_access_orc, columnName:domain}
Time taken: 0.599 seconds, Fetched: 11 row(s)

DEPENDENCY

DEPENDENCY:打印SQL输入表的相关信息

hive (g6_hadoop)> explain DEPENDENCY insert  OVERWRITE table g6_access_orc_explain select domain,count(1) num from g6_access_orc where traffic>'99900' group by domain;
Explain
{"input_partitions":[],"input_tables":[{"tablename":"g6_hadoop@g6_access_orc","tabletype":"MANAGED_TABLE"}]}
Time taken: 0.135 seconds, Fetched: 1 row(s)

以上所述就是小编给大家介绍的《Hive 底层执行流程》，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对码农网的支持！

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