Spark-Sql源码解析之四 Optimizer: analyzed logical plan –> optimized logical plan

Optimizer的主要职责是将Analyzer给Resolved的Logical Plan根据不同的优化策略Batch，来对语法树进行优化，优化逻辑计划节点(Logical Plan)以及表达式(Expression)，也是转换成物理执行计划的前置。它的工作原理和analyzer一致，也是通过其下的batch里面的Rule[LogicalPlan]来进行处理的。

object DefaultOptimizer extends Optimizer {
  val batches =
    // SubQueries are only needed for analysis and can be removed before execution.
    Batch("Remove SubQueries", FixedPoint(100),
      EliminateSubQueries) ::
    Batch("Operator Reordering", FixedPoint(100),
      UnionPushdown,
      //递归合并相邻的两个过滤条件 Filter Pushdown 过滤器下推
      CombineFilters,
      //把从表达式里面的过滤替换成，先做过滤再取表达式，并且掉过滤里面的别名属性
      //典型的例子 select * from (select a,b from table) where a=1
      //替换成select * from (select a,b from table where a=1)
      PushPredicateThroughProject,
      //这个语句可以改写为 select a,b from x where x.a > 0 join (select * from y where y.b >0) on x.id = y.id
      PushPredicateThroughJoin,
      PushPredicateThroughGenerate,
      //去掉一些用不上的列
      ColumnPruning,
      ProjectCollapsing,
      //递归合并相邻的两个limit
    /*
    * select * from (select * from c_picrecord limit 100)a limit 10
    * Limit if ((100 < 10)) 100 else 10
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,ca
    * */
      CombineLimits) ::
    Batch("ConstantFolding", FixedPoint(100),//常量合并
    // 替换null值
    // NullPropagation是一个能将Expression Expressions替换为等价的Literal值的优化，并且能够避免NULL值在SQL语法树的传播。
    NullPropagation,
      OptimizeIn,
      //替换一些简单的常量表达式，比如 1 in (1,2) 直接返回一个true就可以了
      //常量合并是属于Expression优化的一种，对于可以直接计算的常量，不用放到物理执行里去生成对象来计算了，直接可以在计划里就计算出来：
      /*
      * plan->
Project [(((1 + 2) + 3) + 4) AS c0#46]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42,car_numandcolor#43,compare_id#44L,compare_speed#45] org.apache.spark.sql.parquet.ParquetRelation2@6813b117
result->
Project [10 AS c0#46]
 Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42,car_numandcolor#43,compare_id#44L,compare_speed#45] org.apache.spark.sql.parquet.ParquetRelation2@6813b117
rule->
org.apache.spark.sql.catalyst.optimizer.ConstantFolding$@5c99cab8
      *
      * */
      ConstantFolding,
      //简化like语句，避免全表扫描，目前支持'%demo%', '%demo','demo*','demo'
      LikeSimplification,
      //简化过滤条件，比如true and score > 0 直接替换成score > 0
      BooleanSimplification,
      //简化filter，比如where 1=1 或者where 1=2，前者直接去掉这个过滤，后者这个查询就没必要做了
      SimplifyFilters,
      //简化转换，比如两个比较字段的数据类型是一样的，就不需要转换了
      SimplifyCasts,
      //简化大小写转换，比如Upper(Upper('a'))转为认为是Upper('a')
      SimplifyCaseConversionExpressions) ::
    Batch("Decimal Optimizations", FixedPoint(100),
      DecimalAggregates) ::
    Batch("LocalRelation", FixedPoint(100),
      ConvertToLocalRelation) :: Nil
}

接下来讲解几个典型的Rule[LogicalPlan]

4.1 EliminateSubQueries

去除子查询

object EliminateSubQueries extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case Subquery(_, child) => child
  }
}

其实就是把Subquery抹掉，转化为其chcild

例如sql语句如下：

String sql = "SELECT id,dev_chnid,dev_chnname,car_num,car_speed,car_direct from test";

则日志打印如下：

plan->
Project [id#0L,dev_chnid#26,dev_chnname#4,car_num#5,car_speed#8,car_direct#12]
  Subquery test
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [id#0L,dev_chnid#26,dev_chnname#4,car_num#5,car_speed#8,car_direct#12]//去掉Subquery节点
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.analysis.EliminateSubQueries$@7032a1b4

4.2 UnionPushdown

把操作符放置到union的两边

object UnionPushdown extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
  // Push down filter into union
  case Filter(condition, u @ Union(left, right)) =>//把filter放置到union的两边
    val rewrites = buildRewrites(u)
    Union(
      Filter(condition, left),
      Filter(pushToRight(condition, rewrites), right))

  // Push down projection into union
  case Project(projectList, u @ Union(left, right)) =>//把project放置到union的两边
    val rewrites = buildRewrites(u)
    Union(
      Project(projectList, left),
      Project(projectList.map(pushToRight(_, rewrites)), right))
}
}

例如sql语句如下：

String sql = "select * from (select id from test union all select id from test)aa";

则日志打印如下：

plan->
Project [id#0L]
  Union
   Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
   Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
 Union//把project放置到union的两边
  Project [id#0L]
   Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
  Project [id#0L]
   Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.UnionPushdown$@1173be4f

4.3 CombineFilters

合并2个相邻的filter

object CombineFilters extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case ff @ Filter(fc, nf @ Filter(nc, grandChild)) => Filter(And(nc, fc), grandChild)//合并2个filter
  }
}

例如sql语句如下：

String sql = "select id from (select id from test where id >100)a where id > 80";

则日志打印如下：

16-07-22 16:12:16,201 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project
  Filter (id#0L > CAST(80, LongType))
   Filter (id#0L > CAST(100, LongType))
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project
  Filter ((id#0L > CAST(100, LongType)) && (id#0L > CAST(80, LongType)))
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.CombineFilters$@99569a7

4.4 PushPredicateThroughProject

把filter操作符放置到Project里面，即先做过滤，再选择

object PushPredicateThroughProject extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case filter @ Filter(condition, project @ Project(fields, grandChild)) =>
      val sourceAliases = fields.collect { case a @ Alias(c, _) =>
        (a.toAttribute: Attribute) -> c
      }.toMap
      project.copy(child = filter.copy(//把外层的filter放置进project里面
        replaceAlias(condition, sourceAliases),
        grandChild))
  }
  def replaceAlias(condition: Expression, sourceAliases: Map[Attribute, Expression]): Expression = {
    condition transform {
      case a: AttributeReference => sourceAliases.getOrElse(a, a)
    }
  }
}

例如sql语句如下：

String sql = "select * from (select id,car_speed from test)aa where id=1";

则日志打印如下：

16-07-22 16:28:16,850 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [id#0L,car_speed#8]
  Filter (id#0L = CAST(1, LongType))
   Project [id#0L,car_speed#8]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [id#0L,car_speed#8]
  Project [id#0L,car_speed#8]
   Filter (id#0L = CAST(1, LongType))//将filter放置进Project里面
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.PushPredicateThroughProject$@7678c6b4

4.5 PushPredicateThroughJoin

下推filter至join的左边和右边

object PushPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper {
  /**
   * Splits join condition expressions into three categories based on the attributes required
   * to evaluate them.
   * @return (canEvaluateInLeft, canEvaluateInRight, haveToEvaluateInBoth)
   */
  private def split(condition: Seq[Expression], left: LogicalPlan, right: LogicalPlan) = {
    val (leftEvaluateCondition, rest) =
        condition.partition(_.references subsetOf left.outputSet)
    val (rightEvaluateCondition, commonCondition) =
        rest.partition(_.references subsetOf right.outputSet)

    (leftEvaluateCondition, rightEvaluateCondition, commonCondition)
  }

  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    // push the where condition down into join filter
   case f @ Join(left, right, joinType, joinCondition) =>
  val (leftJoinConditions, rightJoinConditions, commonJoinCondition) =
    split(joinCondition.map(splitConjunctivePredicates).getOrElse(Nil), left, right)

  joinType match {
    case _ @ (Inner | LeftSemi) =>
      // push down the single side only join filter for both sides sub queries
      val newLeft = leftJoinConditions.
        reduceLeftOption(And).map(Filter(_, left)).getOrElse(left)
      val newRight = rightJoinConditions.
        reduceLeftOption(And).map(Filter(_, right)).getOrElse(right)
      val newJoinCond = commonJoinCondition.reduceLeftOption(And)

      Join(newLeft, newRight, joinType, newJoinCond)//把部分join的条件下推至其左右两边
      ……
      }
  }
}

例如sql语句如下：

String sql = " select a.id , b.id from test a join test b on a.id = b.id and a.id > 0 and b.id > 0";

则日志打印如下：

16-07-22 17:07:21,526 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [id#0L,id#43L]
  Join Inner, Some((((id#0L = id#43L) && (id#0L > CAST(0, LongType))) && (id#43L > CAST(0, LongType))))
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
Relation[id#43L,dev_id#44,dev_chnnum#45L,dev_name#46,dev_chnname#47,car_num#48,car_numtype#49,car_numcolor#50,car_speed#51,car_type#52,car_color#53,car_length#54L,car_direct#55,car_way_code#56,cap_time#57L,cap_date#58L,inf_note#59,max_speed#60,min_speed#61,car_img_url#62,car_img1_url#63,car_img2_url#64,car_img3_url#65,car_img4_url#66,car_img5_url#67,rec_stat#68,dev_chnid#69,car_img_count#70,save_flag#71,dc_cleanflag#72,pic_id#73,car_img_plate_top#74L,car_img_plate_left#75L,car_img_plate_bottom#76L,car_img_plate_right#77L,car_brand#78L,issafetybelt#79,isvisor#80,bind_stat#81,car_num_pic#82,combined_pic_url#83,verify_memo#84,rec_stat_tmp#85] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Aggregate [COUNT(1) AS count#86L]
 Project [id#0L,id#43L]
  Join Inner, Some((id#0L = id#43L))
   Filter (id#0L > CAST(0, LongType))//先筛选，再做join
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
   Filter (id#43L > CAST(0, LongType)) //先筛选，再做join
Relation[id#43L,dev_id#44,dev_chnnum#45L,dev_name#46,dev_chnname#47,car_num#48,car_numtype#49,car_numcolor#50,car_speed#51,car_type#52,car_color#53,car_length#54L,car_direct#55,car_way_code#56,cap_time#57L,cap_date#58L,inf_note#59,max_speed#60,min_speed#61,car_img_url#62,car_img1_url#63,car_img2_url#64,car_img3_url#65,car_img4_url#66,car_img5_url#67,rec_stat#68,dev_chnid#69,car_img_count#70,save_flag#71,dc_cleanflag#72,pic_id#73,car_img_plate_top#74L,car_img_plate_left#75L,car_img_plate_bottom#76L,car_img_plate_right#77L,car_brand#78L,issafetybelt#79,isvisor#80,bind_stat#81,car_num_pic#82,combined_pic_url#83,verify_memo#84,rec_stat_tmp#85] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.PushPredicateThroughJoin$@6593bce2

4.6 ColumnPruning

裁剪列

object ColumnPruning extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    // Eliminate attributes that are not needed to calculate the specified aggregates.
// select 1+1 as a1, dev_chnid from (select dev_chnid, id from test)a group by dev_chnid
    case a @ Aggregate(_, _, child) if (child.outputSet -- a.references).nonEmpty =>
      a.copy(child = Project(a.references.toSeq, child))//child的输出列多余聚合的列，则进行裁剪
   // select dev_chnid from (select dev_chnid,MAX(id) from test group by dev_chnid)aa
    case p @ Project(projectList, a @ Aggregate(groupingExpressions, aggregateExpressions, child))
        if (a.outputSet -- p.references).nonEmpty =>//只聚合Project需要的列
      Project(
        projectList,
        Aggregate(
          groupingExpressions,
          aggregateExpressions.filter(e => p.references.contains(e)),
          child))
    // Eliminate unneeded attributes from either side of a Join.
//select ai,bi from (select a.id as ai,a.car_speed,b.id as bi,b.car_speed from test a join test b on a.id = b.id)aa
    case Project(projectList, Join(left, right, joinType, condition)) =>//只join Project需要的列
      // Collect the list of all references required either above or to evaluate the condition.
      val allReferences: AttributeSet =
        AttributeSet(
          projectList.flatMap(_.references.iterator)) ++
          condition.map(_.references).getOrElse(AttributeSet(Seq.empty))

      /** Applies a projection only when the child is producing unnecessary attributes */
      def pruneJoinChild(c: LogicalPlan): LogicalPlan = prunedChild(c, allReferences)

      Project(projectList, Join(pruneJoinChild(left), pruneJoinChild(right), joinType, condition))

    // Eliminate unneeded attributes from right side of a LeftSemiJoin.
//select a.*,b.id from test a left join test b on a.id=b.id
    case Join(left, right, LeftSemi, condition) =>//裁剪右节点
      // Collect the list of all references required to evaluate the condition.
      val allReferences: AttributeSet =
        condition.map(_.references).getOrElse(AttributeSet(Seq.empty))

      Join(left, prunedChild(right, allReferences), LeftSemi, condition)
    //select id from (select * from test limit 10)aa
    case Project(projectList, Limit(exp, child)) =>//limit节点上移，供相邻的两个Project节点进行列裁剪
      Limit(exp, Project(projectList, child))

    // push down project if possible when the child is sort
//select * from (select * from test order by id)aa
    case p @ Project(projectList, s @ Sort(_, _, grandChild))//如果sort的表达式是Project的输出的子集，则把Sort上移
      if s.references.subsetOf(p.outputSet) =>
      s.copy(child = Project(projectList, grandChild))

    // Eliminate no-op Projects
    case Project(projectList, child) if child.output == projectList => child//合并没有op的project
  }

例如sql语句如下：

String sql = "SELECT 1+1 as a1, dev_chnid from (select dev_chnid, id from test)a group by dev_chnid";

则日志打印如下：

16-07-23 13:56:17,721 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Aggregate [dev_chnid#26], [(1 + 1) AS a1#43,dev_chnid#26]
 Project [dev_chnid#26,id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Aggregate [dev_chnid#26], [(1 + 1) AS a1#43,dev_chnid#26]
 Project [dev_chnid#26]//只筛选出需要的列
  Project [dev_chnid#26,id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@58b18d61

又比如sql语句如下：

String sql = " select dev_chnid from (select dev_chnid,MAX(id) from test group by dev_chnid)aa";

则日志打印如下：

16-07-23 14:26:37,430 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [dev_chnid#26]
 Aggregate [dev_chnid#26], [dev_chnid#26,MAX(id#0L) AS c1#46L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [dev_chnid#26]
 Aggregate [dev_chnid#26], [dev_chnid#26]//只聚合Project需要的列
  Project [dev_chnid#26]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@70b908c4

又比如sql语句如下：

String sql = "select ai,bi from (select a.id as ai,a.car_speed,b.id as bi,b.car_speed from test a join test b on a.id = b.id)aa";

则日志打印如下：

16-07-23 14:51:05,757 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [id#0L AS ai#49L,id#51L AS bi#50L]
 Join Inner, Some((id#0L = id#51L))
  Project [id#0L,car_speed#8]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
  Project [id#51L,car_speed#59]
Relation[id#51L,dev_id#52,dev_chnnum#53L,dev_name#54,dev_chnname#55,car_num#56,car_numtype#57,car_numcolor#58,car_speed#59,car_type#60,car_color#61,car_length#62L,car_direct#63,car_way_code#64,cap_time#65L,cap_date#66L,inf_note#67,max_speed#68,min_speed#69,car_img_url#70,car_img1_url#71,car_img2_url#72,car_img3_url#73,car_img4_url#74,car_img5_url#75,rec_stat#76,dev_chnid#77,car_img_count#78,save_flag#79,dc_cleanflag#80,pic_id#81,car_img_plate_top#82L,car_img_plate_left#83L,car_img_plate_bottom#84L,car_img_plate_right#85L,car_brand#86L,issafetybelt#87,isvisor#88,bind_stat#89,car_num_pic#90,combined_pic_url#91,verify_memo#92,rec_stat_tmp#93] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [id#0L AS ai#49L,id#51L AS bi#50L]
 Join Inner, Some((id#0L = id#51L))
  Project [id#0L] //只筛选出需要的列
   Project [id#0L,car_speed#8]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
  Project [id#51L] //只筛选出需要的列
   Project [id#51L,car_speed#59]
Relation[id#51L,dev_id#52,dev_chnnum#53L,dev_name#54,dev_chnname#55,car_num#56,car_numtype#57,car_numcolor#58,car_speed#59,car_type#60,car_color#61,car_length#62L,car_direct#63,car_way_code#64,cap_time#65L,cap_date#66L,inf_note#67,max_speed#68,min_speed#69,car_img_url#70,car_img1_url#71,car_img2_url#72,car_img3_url#73,car_img4_url#74,car_img5_url#75,rec_stat#76,dev_chnid#77,car_img_count#78,save_flag#79,dc_cleanflag#80,pic_id#81,car_img_plate_top#82L,car_img_plate_left#83L,car_img_plate_bottom#84L,car_img_plate_right#85L,car_brand#86L,issafetybelt#87,isvisor#88,bind_stat#89,car_num_pic#90,combined_pic_url#91,verify_memo#92,rec_stat_tmp#93] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@3b244fea

又比如sql语句如下：

String sql = " select a.*,b.id from test a left join test b on a.id=b.id";

则日志打印如下：

16-07-23 15:13:23,208 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42,id#43L]
 Join LeftOuter, Some((id#0L = id#43L))
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
Relation[id#43L,dev_id#44,dev_chnnum#45L,dev_name#46,dev_chnname#47,car_num#48,car_numtype#49,car_numcolor#50,car_speed#51,car_type#52,car_color#53,car_length#54L,car_direct#55,car_way_code#56,cap_time#57L,cap_date#58L,inf_note#59,max_speed#60,min_speed#61,car_img_url#62,car_img1_url#63,car_img2_url#64,car_img3_url#65,car_img4_url#66,car_img5_url#67,rec_stat#68,dev_chnid#69,car_img_count#70,save_flag#71,dc_cleanflag#72,pic_id#73,car_img_plate_top#74L,car_img_plate_left#75L,car_img_plate_bottom#76L,car_img_plate_right#77L,car_brand#78L,issafetybelt#79,isvisor#80,bind_stat#81,car_num_pic#82,combined_pic_url#83,verify_memo#84,rec_stat_tmp#85] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42,id#43L]
 Join LeftOuter, Some((id#0L = id#43L))
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
  Project [id#43L] //裁剪右节点
Relation[id#43L,dev_id#44,dev_chnnum#45L,dev_name#46,dev_chnname#47,car_num#48,car_numtype#49,car_numcolor#50,car_speed#51,car_type#52,car_color#53,car_length#54L,car_direct#55,car_way_code#56,cap_time#57L,cap_date#58L,inf_note#59,max_speed#60,min_speed#61,car_img_url#62,car_img1_url#63,car_img2_url#64,car_img3_url#65,car_img4_url#66,car_img5_url#67,rec_stat#68,dev_chnid#69,car_img_count#70,save_flag#71,dc_cleanflag#72,pic_id#73,car_img_plate_top#74L,car_img_plate_left#75L,car_img_plate_bottom#76L,car_img_plate_right#77L,car_brand#78L,issafetybelt#79,isvisor#80,bind_stat#81,car_num_pic#82,combined_pic_url#83,verify_memo#84,rec_stat_tmp#85] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@354ebd72

又比如sql语句如下：

String sql = "select id from (select * from test limit 10)aa";

则日志打印如下：

16-07-23 15:21:26,190 INFO  org.apache.spark.sql.catalyst.optimizer.DefaultOptimizer(Logging.scala:59) ## 
plan->
Project [id#0L]
 Limit 10
Project[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
result->
Limit 10//limit上移
 Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@20a8022

又比如sql语句如下：

String sql = " select * from (select * from test order by id)aa";

则日志打印如下：

plan->
Project [id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42]
 Sort [id#0L ASC], true
  Project [id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42]
   Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Sort [id#0L ASC], true//Sort的表达式id是其父节点的输出，则Sort上移
 Project [id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42]
  Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ColumnPruning$@1aa7d923

4.7 ProjectCollapsing

折叠Project，顾名思义就是把相邻的Project合并成一个Project

object ProjectCollapsing extends Rule[LogicalPlan] {
  /** Returns true if any expression in projectList is non-deterministic. */
  private def hasNondeterministic(projectList: Seq[NamedExpression]): Boolean = {
    projectList.exists(expr => expr.find(!_.deterministic).isDefined)
  }
  def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
    // We only collapse these two Projects if the child Project's expressions are all
    // deterministic.
    case Project(projectList1, Project(projectList2, child))
         if !hasNondeterministic(projectList2) =>
      // Create a map of Aliases to their values from the child projection.
      // e.g., 'SELECT ... FROM (SELECT a + b AS c, d ...)' produces Map(c -> Alias(a + b, c)).
      val aliasMap = AttributeMap(projectList2.collect {
        case a @ Alias(e, _) => (a.toAttribute, a)
      })
      // Substitute any attributes that are produced by the child projection, so that we safely
      // eliminate it.
      // e.g., 'SELECT c + 1 FROM (SELECT a + b AS C ...' produces 'SELECT a + b + 1 ...'
      // TODO: Fix TransformBase to avoid the cast below.
      val substitutedProjection = projectList1.map(_.transform {
        case a: Attribute if aliasMap.contains(a) => aliasMap(a)
      }).asInstanceOf[Seq[NamedExpression]]

      Project(substitutedProjection, child)//合并2个Project的子集
  }
}

例如sql语句如下：

String sql = "select id from (select id,dev_chnid from test)aa";

则日志打印如下：

plan->
Project [id#0L]
 Project [id#0L,dev_chnid#26]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
result->
Project [id#0L]//合并2个相邻的Project
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ProjectCollapsing$@6fe94a75

4.8 CombineLimits

合并2个相邻的limit

object CombineLimits extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    ////ll为当前Limit,le为其expression， nl是ll的grandChild，ne是nl的expression
    case ll @ Limit(le, nl @ Limit(ne, grandChild)) =>
      Limit(If(LessThan(ne, le), ne, le), grandChild)//expression比较，如果ne比le小则表达式为ne，否则为le
  }
}

例如sql语句如下：

String sql = " select id from (select id,dev_chnid from test limit 100)aa limit 10";

则日志打印如下：

plan->
Limit 10
 Limit 100
  Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Limit if ((100 < 10)) 100 else 10//合并2个相邻的Limit
 Project [id#0L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.CombineLimits$@35fb4cf5

4.9 NullPropagation

替换null表达式

object NullPropagation extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case q: LogicalPlan => q transformExpressionsUp {
case e @ Count(Literal(null, _)) => Cast(Literal(0L), e.dataType)//如果count(null)则转化为count(0)
……
}

例如sql语句如下：

String sql = " select COUNT(null) from test";

则日志打印如下：

plan->
Aggregate [COUNT(null) AS c0#43L]
 Project
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Aggregate [CAST(0, LongType) AS c0#43L]//null替换为0
 Project
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.NullPropagation$@44b3ac1f

4.10 OptimizeIn

优化In操作符

object OptimizeIn extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case q: LogicalPlan => q transformExpressionsDown {
      case In(v, list) if !list.exists(!_.isInstanceOf[Literal]) =>
        val hSet = list.map(e => e.eval(null))
        InSet(v, HashSet() ++ hSet)
    }
  }
}

例如sql语句如下：

String sql = "select * from test where id IN(1,2)";

则日志打印如下：

Filter id#0L IN (1,2)
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Filter id#0L INSET (1,2)//将IN优化为INSET
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.OptimizeIn$@33944f6b

4.11 ConstantFolding

合并常量

object ConstantFolding extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {//先对plan进行transform
    case q: LogicalPlan => q transformExpressionsDown { //对每个plan的expression进行transform
      // Skip redundant folding of literals. This rule is technically not necessary. Placing this
      // here avoids running the next rule for Literal values, which would create a new Literal
      // object and running eval unnecessarily.
      case l: Literal => l

      // Fold expressions that are foldable.
      // [ret : 10 | e : (((1 + 2) + 3) + 4) | e.class : class org.apache.spark.sql.catalyst.expressions.Add | e.dataType : (((1 + 2) + 3) + 4).dataType]
      // logInfo(s"[ret : $ret | e : $e | e.class : $eclass | e.dataType : $e.dataType]")
      case e if e.foldable => {
        e.getClass()
        Literal.create(e.eval(null), e.dataType)
      }//调用eval方法计算结果

      // Fold "literal in (item1, item2, ..., literal, ...)" into true directly.
      case In(Literal(v, _), list) if list.exists {
          case Literal(candidate, _) if candidate == v => true
          case _ => false
        } => Literal.create(true, BooleanType)
    }
  }
}

例如sql语句如下：

String sql = " select 1+2+3+id from test";

则日志打印如下：

plan->
Project [(CAST(((1 + 2) + 3), LongType) + id#0L) AS c0#43L]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [(6 + id#0L) AS c0#43L]//合并1+2+3=6
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.ConstantFolding$@4e8a45cd

4.12 LikeSimplification

简化Like表达式

object LikeSimplification extends Rule[LogicalPlan] {
  // if guards below protect from escapes on trailing %.
  // Cases like "something\%" are not optimized, but this does not affect correctness.
  val startsWith = "([^_%]+)%".r
  val endsWith = "%([^_%]+)".r
  val contains = "%([^_%]+)%".r
  val equalTo = "([^_%]*)".r

  def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
    case Like(l, Literal(utf, StringType)) =>
      utf.toString match {
        case startsWith(pattern) if !pattern.endsWith("\\") =>
          StartsWith(l, Literal(pattern))
        case endsWith(pattern) =>
          EndsWith(l, Literal(pattern))
        case contains(pattern) if !pattern.endsWith("\\") =>
          Contains(l, Literal(pattern))
        case equalTo(pattern) =>
          EqualTo(l, Literal(pattern))
        case _ =>
          Like(l, Literal.create(utf, StringType))
      }
  }
}

例如sql语句如下：

String sql = " select * from test where car_num LIKE 'N%'";

则日志打印如下：

plan->
Filter (car_num#5 LIKE N%)
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Filter StartsWith(car_num#5, N)//将N%转换为StartsWith
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
rule->org.apache.spark.sql.catalyst.optimizer.LikeSimplification$@37638d4f

4.13 BooleanSimplification

简化Boolean表达式，就是说如果能预先知道Boolean表达式的值的话，则不计算其他部分了

object BooleanSimplification extends Rule[LogicalPlan] with PredicateHelper {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case q: LogicalPlan => q transformExpressionsUp {
      case and @ And(left, right) => (left, right) match {
        // true && r  =>  r
        case (Literal(true, BooleanType), r) => r//左边为true，则求右边
        // l && true  =>  l
        case (l, Literal(true, BooleanType)) => l//右边为true，则求左边
        // false && r  =>  false
        case (Literal(false, BooleanType), _) => Literal(false)//只要有1个为false，则都为false
        // l && false  =>  false
        case (_, Literal(false, BooleanType)) => Literal(false) //只要有1个为false，则都为false
        // a && a  =>  a
        case (l, r) if l fastEquals r => l//如果左右都相等，则只求1边
        // (a || b) && (a || c)  =>  a || (b && c)
        case _ =>
       ……
}

例如sql语句如下：

String sql = " select * from test where id > 0 and id > 0 and 1 > 0";

则日志打印如下：

plan->
Filter (((id#0L > 0) && (id#0L > 0)) && true)
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Filter (id#0L > 0)
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.BooleanSimplification$@48c9076b

4.14 SimplifyFilters

简化Filter表达式

object SimplifyFilters extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    // If the filter condition always evaluate to true, remove the filter.
    case Filter(Literal(true, BooleanType), child) => child//如果Filter的表达式为true，则去掉Filter
    // If the filter condition always evaluate to null or false,
    // replace the input with an empty relation.
    case Filter(Literal(null, _), child) => LocalRelation(child.output, data = Seq.empty) //如果Filter的表达式为false，则去掉Filter
    case Filter(Literal(false, BooleanType), child) => LocalRelation(child.output, data = Seq.empty)
  }
}

例如sql语句如下：

String sql = " select * from test where 1 > 0";

则日志打印如下：

plan->
Filter true
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010
result->//去除Filter
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.SimplifyFilters$@47fce61b

4.15 SimplifyCasts

简化Cast，如果数据类型和要转换的类型一致，则去掉Cast

object SimplifyCasts extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
    case Cast(e, dataType) if e.dataType == dataType => e//如果类型一致，则去掉Cast
  }
}

例如sql语句如下：

String sql = " select CAST(dev_chnid as String) from test";

则日志打印如下：

plan->
Project [CAST(dev_chnid#26, StringType) AS c0#43]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [dev_chnid#26 AS c0#43]//由于dev_chnid本身就是String，则去掉Cast
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.SimplifyCasts$@2b287e24

4.16 SimplifyCaseConversionExpressions

简化大小写表达式

object SimplifyCaseConversionExpressions extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
    case q: LogicalPlan => q transformExpressionsUp {
      case Upper(Upper(child)) => Upper(child)
      case Upper(Lower(child)) => Upper(child)
      case Lower(Upper(child)) => Lower(child)
      case Lower(Lower(child)) => Lower(child)
    }
  }
}

例如sql语句如下：

String sql = " select UPPER(LOWER(dev_chnid)) from test ";

则日志打印如下：

plan->
Project [Upper(Lower(dev_chnid#26)) AS c0#43]
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

result->
Project [Upper(dev_chnid#26) AS c0#43]//简化大小写表达式
Relation[id#0L,dev_id#1,dev_chnnum#2L,dev_name#3,dev_chnname#4,car_num#5,car_numtype#6,car_numcolor#7,car_speed#8,car_type#9,car_color#10,car_length#11L,car_direct#12,car_way_code#13,cap_time#14L,cap_date#15L,inf_note#16,max_speed#17,min_speed#18,car_img_url#19,car_img1_url#20,car_img2_url#21,car_img3_url#22,car_img4_url#23,car_img5_url#24,rec_stat#25,dev_chnid#26,car_img_count#27,save_flag#28,dc_cleanflag#29,pic_id#30,car_img_plate_top#31L,car_img_plate_left#32L,car_img_plate_bottom#33L,car_img_plate_right#34L,car_brand#35L,issafetybelt#36,isvisor#37,bind_stat#38,car_num_pic#39,combined_pic_url#40,verify_memo#41,rec_stat_tmp#42] org.apache.spark.sql.parquet.ParquetRelation2@2a400010

rule->org.apache.spark.sql.catalyst.optimizer.SimplifyCaseConversionExpressions$@1a09681