Hi Amit;

 �

Thank you for your prompt reply and kind help. Wonder how to set the scheduler 
to FAIR mode in python. Following code seems to me does not work out.

 �

conf = SparkConf().setMaster("local").setAppName("HSMSTest1")

sc = SparkContext(conf=conf)

sc.setLocalProperty('spark.scheduler.mode', 'FAIR')

spark = SparkSession.builder.appName("HSMSStructedStreaming1").getOrCreate()

 �

by the way, as I am using nc -lk 9999 to input the stream, will it cause by the 
reason as the input stream can only be consumed by one query as mentioned in 
below post as;

 �

https://stackoverflow.com/questions/45618489/executing-separate-streaming-queries-in-spark-structured-streaming

 �

appreciate your further help/support.

 �

Best Regards,

 �

Jian Xu

 �

From: Amit Joshi <mailtojoshia...@gmail.com> 
Sent: Friday, May 21, 2021 12:52 PM
To: jia...@xtronica.no
Cc: user@spark.apache.org
Subject: Re: multiple query with structured streaming in spark does not work

 �

Hi Jian,

 �

You have to use same spark session to run all the queries.

And use the following to wait for termination.

 �

q1 = writestream.start

q2 = writstream2.start

spark.streams.awaitAnyTermination

 �

And also set the scheduler in the spark config to FAIR scheduler.

 �

 �

Regards

Amit Joshi

 �



On Saturday, May 22, 2021, <jia...@xtronica.no <mailto:jia...@xtronica.no> > 
wrote:

Hi There;

 �

I am new to spark. We are using spark to develop our app for data streaming 
with sensor readings. 

 �

I am having trouble to get two queries with structured streaming working 
concurrently.

 �

Following is the code. It can only work with one of them. Wonder if there is 
any way to get it doing. Appreciate help from the team.

 �

Regards,

 �

Jian Xu

 �

 �

hostName = 'localhost'

portNumber= 9999

wSize= '10 seconds' 

sSize ='2 seconds'

 �

def wnq_fb_func(batch_df, batch_id):

 � � � print("batch is processed from time:{}".format(datetime.now()))

 � � � print(batch_df.collect())

 � � � batch_df.show(10,False,False)

 � � � 

lines = spark.readStream.format('socket').option('host', 
hostName).option('port', portNumber).option('includeTimestamp', True).load()

 �

nSensors=3

 �

scols = split(lines.value, ',').cast(ArrayType(FloatType()))

sensorCols = []

for i in range(nSensors):

 � � � sensorCols.append(scols.getItem(i).alias('sensor'+ str(i)))

 � � � 

nlines=lines.select(lines.timestamp,lines.value, *sensorCols)

nlines.printSchema()

 �

wnlines =nlines.select(window(nlines.timestamp, wSize, 
sSize).alias('TimeWindow'), *lines.columns)

wnquery= wnlines.writeStream.trigger(processingTime=sSize)\

.outputMode('append').foreachBatch(wnq_fb_func).start()

 �

nquery=nlines.writeStream.outputMode('append').format('console').start()

nquery.awaitTermination()

wnquery.awaitTermination()

 �

 �

 �

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