聊聊flink Table的Joins

序

本文主要研究一下flink Table的Joins

实例

Inner Join

Table left = tableEnv.fromDataSet(ds1, "a, b, c");
Table right = tableEnv.fromDataSet(ds2, "d, e, f");
Table result = left.join(right).where("a = d").select("a, b, e");

• join方法即inner join

Outer Join

Table left = tableEnv.fromDataSet(ds1, "a, b, c");
Table right = tableEnv.fromDataSet(ds2, "d, e, f");

Table leftOuterResult = left.leftOuterJoin(right, "a = d").select("a, b, e");
Table rightOuterResult = left.rightOuterJoin(right, "a = d").select("a, b, e");
Table fullOuterResult = left.fullOuterJoin(right, "a = d").select("a, b, e");

• outer join分为leftOuterJoin、rightOuterJoin、fullOuterJoin三种

Time-windowed Join

Table left = tableEnv.fromDataSet(ds1, "a, b, c, ltime.rowtime");
Table right = tableEnv.fromDataSet(ds2, "d, e, f, rtime.rowtime");

Table result = left.join(right)
  .where("a = d && ltime >= rtime - 5.minutes && ltime < rtime + 10.minutes")
  .select("a, b, e, ltime");

• time-windowed join需要至少一个等值条件，然后还需要一个与两边时间相关的条件(可以使用<, <=, >=, >)

Inner Join with Table Function

// register User-Defined Table Function
TableFunction split = new MySplitUDTF();
tableEnv.registerFunction("split", split);

// join
Table orders = tableEnv.scan("Orders");
Table result = orders
    .join(new Table(tableEnv, "split(c)").as("s", "t", "v"))
    .select("a, b, s, t, v");

• Table也可以跟table function进行inner join，如果table function返回空，则table的记录被丢弃

Left Outer Join with Table Function

// register User-Defined Table Function
TableFunction split = new MySplitUDTF();
tableEnv.registerFunction("split", split);

// join
Table orders = tableEnv.scan("Orders");
Table result = orders
    .leftOuterJoin(new Table(tableEnv, "split(c)").as("s", "t", "v"))
    .select("a, b, s, t, v");

• Table也可以跟table function进行left outer join，如果table function返回空，则table的记录保留，空的部分为null值

Join with Temporal Table

Table ratesHistory = tableEnv.scan("RatesHistory");

// register temporal table function with a time attribute and primary key
TemporalTableFunction rates = ratesHistory.createTemporalTableFunction(
    "r_proctime",
    "r_currency");
tableEnv.registerFunction("rates", rates);

// join with "Orders" based on the time attribute and key
Table orders = tableEnv.scan("Orders");
Table result = orders
    .join(new Table(tEnv, "rates(o_proctime)"), "o_currency = r_currency")

• Table也可以跟Temporal tables进行join，Temporal tables通过Table的createTemporalTableFunction而来，目前仅仅支持inner join的方式

Table

flink-table_2.11-1.7.0-sources.jar!/org/apache/flink/table/api/table.scala

class Table(
    private[flink] val tableEnv: TableEnvironment,
    private[flink] val logicalPlan: LogicalNode) {
  //......

  def join(right: Table): Table = {
    join(right, None, JoinType.INNER)
  }

  def join(right: Table, joinPredicate: String): Table = {
    join(right, joinPredicate, JoinType.INNER)
  }

  def join(right: Table, joinPredicate: Expression): Table = {
    join(right, Some(joinPredicate), JoinType.INNER)
  }

  def leftOuterJoin(right: Table): Table = {
    join(right, None, JoinType.LEFT_OUTER)
  }

  def leftOuterJoin(right: Table, joinPredicate: String): Table = {
    join(right, joinPredicate, JoinType.LEFT_OUTER)
  }

  def leftOuterJoin(right: Table, joinPredicate: Expression): Table = {
    join(right, Some(joinPredicate), JoinType.LEFT_OUTER)
  }

  def rightOuterJoin(right: Table, joinPredicate: String): Table = {
    join(right, joinPredicate, JoinType.RIGHT_OUTER)
  }

  def rightOuterJoin(right: Table, joinPredicate: Expression): Table = {
    join(right, Some(joinPredicate), JoinType.RIGHT_OUTER)
  }

  def fullOuterJoin(right: Table, joinPredicate: String): Table = {
    join(right, joinPredicate, JoinType.FULL_OUTER)
  }

  def fullOuterJoin(right: Table, joinPredicate: Expression): Table = {
    join(right, Some(joinPredicate), JoinType.FULL_OUTER)
  }

  private def join(right: Table, joinPredicate: String, joinType: JoinType): Table = {
    val joinPredicateExpr = ExpressionParser.parseExpression(joinPredicate)
    join(right, Some(joinPredicateExpr), joinType)
  }

  private def join(right: Table, joinPredicate: Option[Expression], joinType: JoinType): Table = {

    // check if we join with a table or a table function
    if (!containsUnboundedUDTFCall(right.logicalPlan)) {
      // regular table-table join

      // check that the TableEnvironment of right table is not null
      // and right table belongs to the same TableEnvironment
      if (right.tableEnv != this.tableEnv) {
        throw new ValidationException("Only tables from the same TableEnvironment can be joined.")
      }

      new Table(
        tableEnv,
        Join(this.logicalPlan, right.logicalPlan, joinType, joinPredicate, correlated = false)
          .validate(tableEnv))

    } else {
      // join with a table function

      // check join type
      if (joinType != JoinType.INNER && joinType != JoinType.LEFT_OUTER) {
        throw new ValidationException(
          "TableFunctions are currently supported for join and leftOuterJoin.")
      }

      val udtf = right.logicalPlan.asInstanceOf[LogicalTableFunctionCall]
      val udtfCall = LogicalTableFunctionCall(
        udtf.functionName,
        udtf.tableFunction,
        udtf.parameters,
        udtf.resultType,
        udtf.fieldNames,
        this.logicalPlan
      ).validate(tableEnv)

      new Table(
        tableEnv,
        Join(this.logicalPlan, udtfCall, joinType, joinPredicate, correlated = true)
          .validate(tableEnv))
    }
  }

  //......
}

• Table定义了join、leftOuterJoin、rightOuterJoin、fullOuterJoin方法，其最后都是调用的私有的join方法，其中JoinType用于表达join类型，分别有INNER, LEFT_OUTER, RIGHT_OUTER, FULL_OUTER这几种；另外接收String类型或者Expression的条件表达式，其中String类型最后是被解析为Expression类型；join方法最后是使用Join创建了新的Table

Join

flink-table_2.11-1.7.0-sources.jar!/org/apache/flink/table/plan/logical/operators.scala

case class Join(
    left: LogicalNode,
    right: LogicalNode,
    joinType: JoinType,
    condition: Option[Expression],
    correlated: Boolean) extends BinaryNode {

  override def output: Seq[Attribute] = {
    left.output ++ right.output
  }

  private case class JoinFieldReference(
    name: String,
    resultType: TypeInformation[_],
    left: LogicalNode,
    right: LogicalNode) extends Attribute {

    val isFromLeftInput: Boolean = left.output.map(_.name).contains(name)

    val (indexInInput, indexInJoin) = if (isFromLeftInput) {
      val indexInLeft = left.output.map(_.name).indexOf(name)
      (indexInLeft, indexInLeft)
    } else {
      val indexInRight = right.output.map(_.name).indexOf(name)
      (indexInRight, indexInRight + left.output.length)
    }

    override def toString = s"'$name"

    override def toRexNode(implicit relBuilder: RelBuilder): RexNode = {
      // look up type of field
      val fieldType = relBuilder.field(2, if (isFromLeftInput) 0 else 1, name).getType
      // create a new RexInputRef with index offset
      new RexInputRef(indexInJoin, fieldType)
    }

    override def withName(newName: String): Attribute = {
      if (newName == name) {
        this
      } else {
        JoinFieldReference(newName, resultType, left, right)
      }
    }
  }

  override def resolveExpressions(tableEnv: TableEnvironment): LogicalNode = {
    val node = super.resolveExpressions(tableEnv).asInstanceOf[Join]
    val partialFunction: PartialFunction[Expression, Expression] = {
      case field: ResolvedFieldReference => JoinFieldReference(
        field.name,
        field.resultType,
        left,
        right)
    }
    val resolvedCondition = node.condition.map(_.postOrderTransform(partialFunction))
    Join(node.left, node.right, node.joinType, resolvedCondition, correlated)
  }

  override protected[logical] def construct(relBuilder: RelBuilder): RelBuilder = {
    left.construct(relBuilder)
    right.construct(relBuilder)

    val corSet = mutable.Set[CorrelationId]()
    if (correlated) {
      corSet += relBuilder.peek().getCluster.createCorrel()
    }

    relBuilder.join(
      convertJoinType(joinType),
      condition.map(_.toRexNode(relBuilder)).getOrElse(relBuilder.literal(true)),
      corSet.asJava)
  }

  private def convertJoinType(joinType: JoinType) = joinType match {
    case JoinType.INNER => JoinRelType.INNER
    case JoinType.LEFT_OUTER => JoinRelType.LEFT
    case JoinType.RIGHT_OUTER => JoinRelType.RIGHT
    case JoinType.FULL_OUTER => JoinRelType.FULL
  }

  private def ambiguousName: Set[String] =
    left.output.map(_.name).toSet.intersect(right.output.map(_.name).toSet)

  override def validate(tableEnv: TableEnvironment): LogicalNode = {
    val resolvedJoin = super.validate(tableEnv).asInstanceOf[Join]
    if (!resolvedJoin.condition.forall(_.resultType == BOOLEAN_TYPE_INFO)) {
      failValidation(s"Filter operator requires a boolean expression as input, " +
        s"but ${resolvedJoin.condition} is of type ${resolvedJoin.joinType}")
    } else if (ambiguousName.nonEmpty) {
      failValidation(s"join relations with ambiguous names: ${ambiguousName.mkString(", ")}")
    }

    resolvedJoin.condition.foreach(testJoinCondition)
    resolvedJoin
  }

  private def testJoinCondition(expression: Expression): Unit = {

    def checkIfJoinCondition(exp: BinaryComparison) = exp.children match {
      case (x: JoinFieldReference) :: (y: JoinFieldReference) :: Nil
        if x.isFromLeftInput != y.isFromLeftInput => true
      case _ => false
    }

    def checkIfFilterCondition(exp: BinaryComparison) = exp.children match {
      case (x: JoinFieldReference) :: (y: JoinFieldReference) :: Nil => false
      case (x: JoinFieldReference) :: (_) :: Nil => true
      case (_) :: (y: JoinFieldReference) :: Nil => true
      case _ => false
    }

    var equiJoinPredicateFound = false
    // Whether the predicate is literal true.
    val alwaysTrue = expression match {
      case x: Literal if x.value.equals(true) => true
      case _ => false
    }

    def validateConditions(exp: Expression, isAndBranch: Boolean): Unit = exp match {
      case x: And => x.children.foreach(validateConditions(_, isAndBranch))
      case x: Or => x.children.foreach(validateConditions(_, isAndBranch = false))
      case x: EqualTo =>
        if (isAndBranch && checkIfJoinCondition(x)) {
          equiJoinPredicateFound = true
        }
      case x: BinaryComparison =>
      // The boolean literal should be a valid condition type.
      case x: Literal if x.resultType == Types.BOOLEAN =>
      case x => failValidation(
        s"Unsupported condition type: ${x.getClass.getSimpleName}. Condition: $x")
    }

    validateConditions(expression, isAndBranch = true)

    // Due to a bug in Apache Calcite (see CALCITE-2004 and FLINK-7865) we cannot accept join
    // predicates except literal true for TableFunction left outer join.
    if (correlated && right.isInstanceOf[LogicalTableFunctionCall] && joinType != JoinType.INNER ) {
      if (!alwaysTrue) failValidation("TableFunction left outer join predicate can only be " +
        "empty or literal true.")
    } else {
      if (!equiJoinPredicateFound) {
        failValidation(
          s"Invalid join condition: $expression. At least one equi-join predicate is " +
            s"required.")
      }
    }
  }
}

• Join继承了BinaryNode，它内部将flink的JoinType转为calcite的JoinRelType类型，construct方法通过relBuilder.join来构建join关系

小结

• Table支持多种形式的join，其中包括Inner Join、Outer Join、Time-windowed Join、Inner Join with Table Function、Left Outer Join with Table Function、Join with Temporal Table
• Table定义了join、leftOuterJoin、rightOuterJoin、fullOuterJoin方法，其最后都是调用的私有的join方法，其中JoinType用于表达join类型，分别有INNER, LEFT_OUTER, RIGHT_OUTER, FULL_OUTER这几种；另外接收String类型或者Expression的条件表达式，其中String类型最后是被解析为Expression类型；join方法最后是使用Join创建了新的Table
• Join继承了BinaryNode，它内部将flink的JoinType转为calcite的JoinRelType类型，construct方法通过relBuilder.join来构建join关系

doc

• Joins