序
本文主要研究一下flink Table的Group Windows
实例
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w") // group the table by window w
.select("b.sum"); // aggregate
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w, a") // group the table by attribute a and window w
.select("a, b.sum"); // aggregate
Table table = input
.window([Window w].as("w")) // define window with alias w
.groupBy("w, a") // group the table by attribute a and window w
.select("a, w.start, w.end, w.rowtime, b.count"); // aggregate and add window start, end, and rowtime timestamps
- window操作可以对Window进行别名，然后可以在groupBy及select中引用，window有start、end、rowtime属性可以用，其中start及rowtime是inclusive的，而end为exclusive
Tumbling Windows实例
// Tumbling Event-time Window
.window(Tumble.over("10.minutes").on("rowtime").as("w"));
// Tumbling Processing-time Window (assuming a processing-time attribute "proctime")
.window(Tumble.over("10.minutes").on("proctime").as("w"));
// Tumbling Row-count Window (assuming a processing-time attribute "proctime")
.window(Tumble.over("10.rows").on("proctime").as("w"));
- Tumbling Windows按固定窗口大小来移动，因而窗口不重叠；over方法用于指定窗口大小；窗口大小可以基于event-time、processing-time、row-count来定义
Sliding Windows实例
// Sliding Event-time Window
.window(Slide.over("10.minutes").every("5.minutes").on("rowtime").as("w"));
// Sliding Processing-time window (assuming a processing-time attribute "proctime")
.window(Slide.over("10.minutes").every("5.minutes").on("proctime").as("w"));
// Sliding Row-count window (assuming a processing-time attribute "proctime")
.window(Slide.over("10.rows").every("5.rows").on("proctime").as("w"));
- Sliding Windows在slide interval小于window size的时候，窗口会有重叠，因而rows可能归属多个窗口；over方法用于指定窗口大小，窗口大小可以基于event-time、processing-time、row-count来定义；every方法用于指定slide interval
Session Windows实例
// Session Event-time Window
.window(Session.withGap("10.minutes").on("rowtime").as("w"));
// Session Processing-time Window (assuming a processing-time attribute "proctime")
.window(Session.withGap("10.minutes").on("proctime").as("w"));
- Session Windows没有固定的窗口大小，它基于inactivity的程度来关闭窗口，withGap方法用于指定两个窗口的gap，作为time interval；Session Windows只能使用event-time或者processing-time
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) {
//......
def window(window: Window): WindowedTable = {
new WindowedTable(this, window)
}
//......
}
- Table提供了window操作，接收Window参数，创建的是WindowedTable
WindowedTable
flink-table_2.11-1.7.0-sources.jar!/org/apache/flink/table/api/table.scala
class WindowedTable(
private[flink] val table: Table,
private[flink] val window: Window) {
def groupBy(fields: Expression*): WindowGroupedTable = {
val fieldsWithoutWindow = fields.filterNot(window.alias.equals(_))
if (fields.size != fieldsWithoutWindow.size + 1) {
throw new ValidationException("GroupBy must contain exactly one window alias.")
}
new WindowGroupedTable(table, fieldsWithoutWindow, window)
}
def groupBy(fields: String): WindowGroupedTable = {
val fieldsExpr = ExpressionParser.parseExpressionList(fields)
groupBy(fieldsExpr: _*)
}
}
- WindowedTable只提供groupBy操作，其中groupBy可以接收String类型的参数，也可以接收Expression类型的参数；String类型的参数会被转换为Expression类型，最后调用的是Expression类型参数的groupBy方法；如果groupBy除了window没有其他属性，则其parallelism为1，只会在单一task上执行；groupBy方法创建的是WindowGroupedTable
WindowGroupedTable
flink-table_2.11-1.7.0-sources.jar!/org/apache/flink/table/api/table.scala
class WindowGroupedTable(
private[flink] val table: Table,
private[flink] val groupKeys: Seq[Expression],
private[flink] val window: Window) {
def select(fields: Expression*): Table = {
val expandedFields = expandProjectList(fields, table.logicalPlan, table.tableEnv)
val (aggNames, propNames) = extractAggregationsAndProperties(expandedFields, table.tableEnv)
val projectsOnAgg = replaceAggregationsAndProperties(
expandedFields, table.tableEnv, aggNames, propNames)
val projectFields = extractFieldReferences(expandedFields ++ groupKeys :+ window.timeField)
new Table(table.tableEnv,
Project(
projectsOnAgg,
WindowAggregate(
groupKeys,
window.toLogicalWindow,
propNames.map(a => Alias(a._1, a._2)).toSeq,
aggNames.map(a => Alias(a._1, a._2)).toSeq,
Project(projectFields, table.logicalPlan).validate(table.tableEnv)
).validate(table.tableEnv),
// required for proper resolution of the time attribute in multi-windows
explicitAlias = true
).validate(table.tableEnv))
}
def select(fields: String): Table = {
val fieldExprs = ExpressionParser.parseExpressionList(fields)
//get the correct expression for AggFunctionCall
val withResolvedAggFunctionCall = fieldExprs.map(replaceAggFunctionCall(_, table.tableEnv))
select(withResolvedAggFunctionCall: _*)
}
}
- WindowGroupedTable只提供select操作，其中select可以接收String类型的参数，也可以接收Expression类型的参数；String类型的参数会被转换为Expression类型，最后调用的是Expression类型参数的select方法；select方法创建了新的Table，其Project的child为WindowAggregate
小结
- window操作可以对Window进行别名，然后可以在groupBy及select中引用，window有start、end、rowtime属性可以用，其中start及rowtime是inclusive的，而end为exclusive
- Tumbling Windows按固定窗口大小来移动，因而窗口不重叠；over方法用于指定窗口大小；窗口大小可以基于event-time、processing-time、row-count来定义；Sliding Windows在slide interval小于window size的时候，窗口会有重叠，因而rows可能归属多个窗口；over方法用于指定窗口大小，窗口大小可以基于event-time、processing-time、row-count来定义；every方法用于指定slide interval；Session Windows没有固定的窗口大小，它基于inactivity的程度来关闭窗口，withGap方法用于指定两个窗口的gap，作为time interval；Session Windows只能使用event-time或者processing-time
- Table提供了window操作，接收Window参数，创建的是WindowedTable；WindowedTable只提供groupBy操作，其中groupBy可以接收String类型的参数，也可以接收Expression类型的参数；String类型的参数会被转换为Expression类型，最后调用的是Expression类型参数的groupBy方法；如果groupBy除了window没有其他属性，则其parallelism为1，只会在单一task上执行；groupBy方法创建的是WindowGroupedTable；WindowGroupedTable只提供select操作，其中select可以接收String类型的参数，也可以接收Expression类型的参数；String类型的参数会被转换为Expression类型，最后调用的是Expression类型参数的select方法；select方法创建了新的Table，其Project的child为WindowAggregate
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