I have been testing some with aggregations, but I seem to hit a wall on two
issues.
example:
val avg = areaStateDf.groupBy($"plantKey").avg("sensor")
1) How can I use the result from an aggr within the same stream, to do further
calculations?
2) It seems to be very slow. If I want a moving window of 24 hours, and to have
a moving average on some calculations within this. When testing locally with
using
The Accumulator issue:
Simple Counter Accumulator:
object Test {
private val spark = SparkHelper.getSparkSession()
import spark.implicits._
import com.datastax.spark.connector._
val counter = spark.sparkContext.longAccumulator("counter")
val fetchData = () => {
counter.add(2)
counter.value
}
val fetchdataUDF = spark.sqlContext.udf.register("testUDF", fetchData)
def calculate(areaStateDf: DataFrame): StreamingQuery = {
import spark.implicits._
val ds = areaStateDf.select($"areaKey").withColumn("fetchedData",
fetchdataUDF())
KafkaSinks.debugStream(ds, "volumTest")
}
}
I would create a custom accumulator to include a smoothing algorithm, but cant
seem to be able to get a normal counter working.
This works locally, but on the server running Docker (using a master and 1
worker) throws this error:
18/05/16 08:35:22 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 3.0
(TID 3, 172.17.0.5, executor 0): java.lang.ExceptionInInitializerError
at com.client.spark.calculations.Test$$anonfun$1.apply(ThpLoad1.scala:24)
at com.client.spark.calculations.Test$$anonfun$1.apply(ThpLoad1.scala:15)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:235)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: A master URL must be set in your
configuration
at org.apache.spark.SparkContext.<init>(SparkContext.scala:376)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
at
org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:918)
at
org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:910)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:910)
at com.cambi.assurance.spark.SparkHelper$.getSparkSession(SparkHelper.scala:28)
at com.client.spark.calculations.Test$.<init>(ThpLoad1.scala:10)
at com.client.spark.calculations.Test$.<clinit>(ThpLoad1.scala)
... 18 more
18/05/16 08:35:22 WARN scheduler.TaskSetManager: Lost task 0.1 in stage 3.0
(TID 4, 172.17.0.5, executor 0): java.lang.NoClassDefFoundError: Could not
initialize class com.client.spark.calculations.Test$
at com.client.spark.calculations.Test$$anonfun$1.apply(ThpLoad1.scala:24)
at com.client.spark.calculations.Test$$anonfun$1.apply(ThpLoad1.scala:15)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:235)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
Any ideas about how to handle this error?
Thanks,
Martin Engen
________________________________
From: Lalwani, Jayesh <jayesh.lalw...@capitalone.com>
Sent: Tuesday, May 15, 2018 9:59 PM
To: Martin Engen; user@spark.apache.org
Subject: Re: Structured Streaming, Reading and Updating a variable
Do you have a code sample, and detailed error message/exception to show?
From: Martin Engen <martin.en...@outlook.com>
Date: Tuesday, May 15, 2018 at 9:24 AM
To: "user@spark.apache.org" <user@spark.apache.org>
Subject: Structured Streaming, Reading and Updating a variable
Hello,
I'm working with Structured Streaming, and I need a method of keeping a running
average based on last 24hours of data.
To help with this, I can use Exponential Smoothing, which means I really only
need to store 1 value from a previous calculation into the new, and update this
variable as calculations carry on.
Implementing this is a much bigger challenge then I ever imagined.
I've tried using Accumulators and to Query/Store data to Cassandra after every
calculation. Both methods worked somewhat locally , but I don't seem to be able
to use these in the Spark Worker Nodes, as I get the error
"java.lang.NoClassDefFoundError: Could not initialize class error" both for the
accumulator and the cassandra connection libary
How can you read/update a variable while doing calculations using Structured
Streaming?
Thank you
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