
org.apache.spark.sql.execution.streaming.Triggers.scala Maven / Gradle / Ivy
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package org.apache.spark.sql.execution.streaming
import java.util.concurrent.TimeUnit
import scala.concurrent.duration.Duration
import org.apache.spark.sql.catalyst.util.DateTimeConstants.MICROS_PER_DAY
import org.apache.spark.sql.catalyst.util.DateTimeUtils.toMillis
import org.apache.spark.sql.catalyst.util.IntervalUtils
import org.apache.spark.sql.streaming.Trigger
import org.apache.spark.unsafe.types.UTF8String
private object Triggers {
def validate(intervalMs: Long): Unit = {
require(intervalMs >= 0, "the interval of trigger should not be negative")
}
def convert(interval: String): Long = {
val cal = IntervalUtils.stringToInterval(UTF8String.fromString(interval))
if (cal.months != 0) {
throw new IllegalArgumentException(s"Doesn't support month or year interval: $interval")
}
val microsInDays = Math.multiplyExact(cal.days, MICROS_PER_DAY)
toMillis(Math.addExact(cal.microseconds, microsInDays))
}
def convert(interval: Duration): Long = interval.toMillis
def convert(interval: Long, unit: TimeUnit): Long = unit.toMillis(interval)
}
/**
* A [[Trigger]] that processes only one batch of data in a streaming query then terminates
* the query.
*/
case object OneTimeTrigger extends Trigger
/**
* A [[Trigger]] that runs a query periodically based on the processing time. If `interval` is 0,
* the query will run as fast as possible.
*/
case class ProcessingTimeTrigger(intervalMs: Long) extends Trigger {
Triggers.validate(intervalMs)
}
object ProcessingTimeTrigger {
import Triggers._
def apply(interval: String): ProcessingTimeTrigger = {
ProcessingTimeTrigger(convert(interval))
}
def apply(interval: Duration): ProcessingTimeTrigger = {
ProcessingTimeTrigger(convert(interval))
}
def create(interval: String): ProcessingTimeTrigger = {
apply(interval)
}
def create(interval: Long, unit: TimeUnit): ProcessingTimeTrigger = {
ProcessingTimeTrigger(convert(interval, unit))
}
}
/**
* A [[Trigger]] that continuously processes streaming data, asynchronously checkpointing at
* the specified interval.
*/
case class ContinuousTrigger(intervalMs: Long) extends Trigger {
Triggers.validate(intervalMs)
}
object ContinuousTrigger {
import Triggers._
def apply(interval: String): ContinuousTrigger = {
ContinuousTrigger(convert(interval))
}
def apply(interval: Duration): ContinuousTrigger = {
ContinuousTrigger(convert(interval))
}
def create(interval: String): ContinuousTrigger = {
apply(interval)
}
def create(interval: Long, unit: TimeUnit): ContinuousTrigger = {
ContinuousTrigger(convert(interval, unit))
}
}
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