聊聊flink Table的Over Windows

序

本文主要研究一下flink Table的Over Windows

实例

Table table = input
  .window([OverWindow w].as("w"))           // define over window with alias w
  .select("a, b.sum over w, c.min over w"); // aggregate over the over window w

Over Windows类似SQL的over子句，它可以基于event-time、processing-time或者row-count；具体可以通过Over类来构造，其中必须设置orderBy、preceding及as方法；它有Unbounded及Bounded两大类

Unbounded Over Windows实例


// Unbounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("unbounded_range").as("w"));

// Unbounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("unbounded_range").as("w"));

// Unbounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("unbounded_row").as("w"));
 
// Unbounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("unbounded_row").as("w"));

对于event-time及processing-time使用unbounded_range来表示Unbounded，对于row-count使用unbounded_row来表示Unbounded

Bounded Over Windows实例

// Bounded Event-time over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("1.minutes").as("w"))

// Bounded Processing-time over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("1.minutes").as("w"))

// Bounded Event-time Row-count over window (assuming an event-time attribute "rowtime")
.window(Over.partitionBy("a").orderBy("rowtime").preceding("10.rows").as("w"))
 
// Bounded Processing-time Row-count over window (assuming a processing-time attribute "proctime")
.window(Over.partitionBy("a").orderBy("proctime").preceding("10.rows").as("w"))

对于event-time及processing-time使用诸如1.minutes来表示Bounded，对于row-count使用诸如10.rows来表示Bounded

Table.window

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) {

  //......  

  @varargs
  def window(overWindows: OverWindow*): OverWindowedTable = {

    if (tableEnv.isInstanceOf[BatchTableEnvironment]) {
      throw new TableException("Over-windows for batch tables are currently not supported.")
    }

    if (overWindows.size != 1) {
      throw new TableException("Over-Windows are currently only supported single window.")
    }

    new OverWindowedTable(this, overWindows.toArray)
  }

  //......

}

Table提供了OverWindow参数的window方法，用来进行Over Windows操作，它创建的是OverWindowedTable

OverWindow

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

/**
  * Over window is similar to the traditional OVER SQL.
  */
case class OverWindow(
    private[flink] val alias: Expression,
    private[flink] val partitionBy: Seq[Expression],
    private[flink] val orderBy: Expression,
    private[flink] val preceding: Expression,
    private[flink] val following: Expression)

OverWindow定义了alias、partitionBy、orderBy、preceding、following属性

Over

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

object Over {

  /**
    * Specifies the time attribute on which rows are grouped.
    *
    * For streaming tables call [[orderBy 'rowtime or orderBy 'proctime]] to specify time mode.
    *
    * For batch tables, refer to a timestamp or long attribute.
    */
  def orderBy(orderBy: String): OverWindowWithOrderBy = {
    val orderByExpr = ExpressionParser.parseExpression(orderBy)
    new OverWindowWithOrderBy(Array[Expression](), orderByExpr)
  }

  /**
    * Partitions the elements on some partition keys.
    *
    * @param partitionBy some partition keys.
    * @return A partitionedOver instance that only contains the orderBy method.
    */
  def partitionBy(partitionBy: String): PartitionedOver = {
    val partitionByExpr = ExpressionParser.parseExpressionList(partitionBy).toArray
    new PartitionedOver(partitionByExpr)
  }
}

class OverWindowWithOrderBy(
  private val partitionByExpr: Array[Expression],
  private val orderByExpr: Expression) {

  /**
    * Set the preceding offset (based on time or row-count intervals) for over window.
    *
    * @param preceding preceding offset relative to the current row.
    * @return this over window
    */
  def preceding(preceding: String): OverWindowWithPreceding = {
    val precedingExpr = ExpressionParser.parseExpression(preceding)
    new OverWindowWithPreceding(partitionByExpr, orderByExpr, precedingExpr)
  }

}

class PartitionedOver(private val partitionByExpr: Array[Expression]) {

  /**
    * Specifies the time attribute on which rows are grouped.
    *
    * For streaming tables call [[orderBy 'rowtime or orderBy 'proctime]] to specify time mode.
    *
    * For batch tables, refer to a timestamp or long attribute.
    */
  def orderBy(orderBy: String): OverWindowWithOrderBy = {
    val orderByExpr = ExpressionParser.parseExpression(orderBy)
    new OverWindowWithOrderBy(partitionByExpr, orderByExpr)
  }
}

class OverWindowWithPreceding(
    private val partitionBy: Seq[Expression],
    private val orderBy: Expression,
    private val preceding: Expression) {

  private[flink] var following: Expression = _

  /**
    * Assigns an alias for this window that the following `select()` clause can refer to.
    *
    * @param alias alias for this over window
    * @return over window
    */
  def as(alias: String): OverWindow = as(ExpressionParser.parseExpression(alias))

  /**
    * Assigns an alias for this window that the following `select()` clause can refer to.
    *
    * @param alias alias for this over window
    * @return over window
    */
  def as(alias: Expression): OverWindow = {

    // set following to CURRENT_ROW / CURRENT_RANGE if not defined
    if (null == following) {
      if (preceding.resultType.isInstanceOf[RowIntervalTypeInfo]) {
        following = CURRENT_ROW
      } else {
        following = CURRENT_RANGE
      }
    }
    OverWindow(alias, partitionBy, orderBy, preceding, following)
  }

  /**
    * Set the following offset (based on time or row-count intervals) for over window.
    *
    * @param following following offset that relative to the current row.
    * @return this over window
    */
  def following(following: String): OverWindowWithPreceding = {
    this.following(ExpressionParser.parseExpression(following))
  }

  /**
    * Set the following offset (based on time or row-count intervals) for over window.
    *
    * @param following following offset that relative to the current row.
    * @return this over window
    */
  def following(following: Expression): OverWindowWithPreceding = {
    this.following = following
    this
  }
}

Over类是创建over window的帮助类，它提供了orderBy及partitionBy两个方法，分别创建的是OverWindowWithOrderBy及PartitionedOver
PartitionedOver提供了orderBy方法，创建的是OverWindowWithOrderBy；OverWindowWithOrderBy提供了preceding方法，创建的是OverWindowWithPreceding
OverWindowWithPreceding则包含了partitionBy、orderBy、preceding属性，它提供了as方法创建OverWindow，另外还提供了following方法用于设置following offset

OverWindowedTable