本文主要研究一下flink Table的Group Windows
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
// 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"));
// 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"));
// 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"));
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)
}
//......
}
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: _*)
}
}
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: _*)
}
}
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。