Spark 3.0.0 ScalaDoc < Back

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package root

Definition Classes
root
package org

Definition Classes
root
package apache

Definition Classes
org
package spark
Core Spark functionality.
Core Spark functionality. org.apache.spark.SparkContext serves as the main entry point to Spark, while org.apache.spark.rdd.RDD is the data type representing a distributed collection, and provides most parallel operations.
In addition, org.apache.spark.rdd.PairRDDFunctions contains operations available only on RDDs of key-value pairs, such as groupByKey and join; org.apache.spark.rdd.DoubleRDDFunctions contains operations available only on RDDs of Doubles; and org.apache.spark.rdd.SequenceFileRDDFunctions contains operations available on RDDs that can be saved as SequenceFiles. These operations are automatically available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit conversions.
Java programmers should reference the org.apache.spark.api.java package for Spark programming APIs in Java.
Classes and methods marked with Experimental are user-facing features which have not been officially adopted by the Spark project. These are subject to change or removal in minor releases.
Classes and methods marked with Developer API are intended for advanced users want to extend Spark through lower level interfaces. These are subject to changes or removal in minor releases.

Definition Classes
apache
package sql
Allows the execution of relational queries, including those expressed in SQL using Spark.
Allows the execution of relational queries, including those expressed in SQL using Spark.

Definition Classes
spark
package streaming

Definition Classes
sql
DataStreamReader
DataStreamWriter
GroupState
GroupStateTimeout
OutputMode
ProcessingTime
SinkProgress
SourceProgress
StateOperatorProgress
StreamingQuery
StreamingQueryException
StreamingQueryListener
StreamingQueryManager
StreamingQueryProgress
StreamingQueryStatus
Trigger

org.apache.spark.sql.streaming

ProcessingTime

Companion class ProcessingTime

object ProcessingTime extends Serializable

Used to create ProcessingTime triggers for StreamingQuerys.

Annotations: @Evolving() @deprecated
Deprecated: (Since version 2.2.0) use Trigger.ProcessingTime(intervalMs)
Since: 2.0.0

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Serializable, Serializable, AnyRef, Any

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Deprecated Value Members

def apply(interval: Duration): ProcessingTime
Create a ProcessingTime.
Create a ProcessingTime. If interval is 0, the query will run as fast as possible.
Example:
```
import scala.concurrent.duration._
df.writeStream.trigger(ProcessingTime(10.seconds))
```
Annotations
@deprecated
Deprecated
(Since version 2.2.0) use Trigger.ProcessingTime(interval)
Since
2.0.0
def apply(interval: String): ProcessingTime
Create a ProcessingTime.
Create a ProcessingTime. If interval is 0, the query will run as fast as possible.
Example:
```
df.writeStream.trigger(ProcessingTime("10 seconds"))
```
Annotations
@deprecated
Deprecated
(Since version 2.2.0) use Trigger.ProcessingTime(interval)
Since
2.0.0
def create(interval: Long, unit: TimeUnit): ProcessingTime
Create a ProcessingTime.
Create a ProcessingTime. If interval is 0, the query will run as fast as possible.
Example:
```
import java.util.concurrent.TimeUnit
df.writeStream.trigger(ProcessingTime.create(10, TimeUnit.SECONDS))
```
Annotations
@deprecated
Deprecated
(Since version 2.2.0) use Trigger.ProcessingTime(interval, unit)
Since
2.0.0
def create(interval: String): ProcessingTime
Create a ProcessingTime.
Create a ProcessingTime. If interval is 0, the query will run as fast as possible.
Example:
```
df.writeStream.trigger(ProcessingTime.create("10 seconds"))
```
Annotations
@deprecated
Deprecated
(Since version 2.2.0) use Trigger.ProcessingTime(interval)
Since
2.0.0

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