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From spark receiver <spark.recei...@gmail.com>
Subject Re: [Structured Streaming] More than 1 streaming in a code
Date Sat, 14 Apr 2018 03:49:06 GMT
Hi Panagiotis ,

Wondering you solved the problem or not? Coz I met the same issue today. I’d appreciate
 so much if you could paste the code snippet  if it’s working .

Thanks.


> 在 2018年4月6日,上午7:40,Aakash Basu <aakash.spark.raj@gmail.com> 写道:
> 
> Hi Panagiotis,
> 
> I did that, but it still prints the result of the first query and awaits for new data,
doesn't even goes to the next one.
> 
> Data -
> 
> $ nc -lk 9998
> 
> 1,2
> 3,4
> 5,6
> 7,8
> 
> Result -
> 
> -------------------------------------------
> Batch: 0
> -------------------------------------------
> +----+
> |aver|
> +----+
> | 3.0|
> +----+
> 
> -------------------------------------------
> Batch: 1
> -------------------------------------------
> +----+
> |aver|
> +----+
> | 4.0|
> +----+
> 
> 
> Updated Code -
> from pyspark.sql import SparkSession
> from pyspark.sql.functions import split
> 
> spark = SparkSession \
>     .builder \
>     .appName("StructuredNetworkWordCount") \
>     .getOrCreate()
> 
> data = spark \
>     .readStream \
>     .format("socket") \
>     .option("header","true") \
>     .option("host", "localhost") \
>     .option("port", 9998) \
>     .load("csv")
> 
> 
> id_DF = data.select(split(data.value, ",").getItem(0).alias("col1"), split(data.value,
",").getItem(1).alias("col2"))
> 
> id_DF.createOrReplaceTempView("ds")
> 
> df = spark.sql("select avg(col1) as aver from ds")
> 
> df.createOrReplaceTempView("abcd")
> 
> wordCounts = spark.sql("Select col1, col2, col2/(select aver from abcd) col3 from ds")
 # (select aver from abcd)
> 
> query2 = df \
>     .writeStream \
>     .format("console") \
>     .outputMode("complete") \
>     .trigger(processingTime='5 seconds') \
>     .start()
> 
> query = wordCounts \
>     .writeStream \
>     .format("console") \
>     .trigger(processingTime='5 seconds') \
>     .start()
> 
> spark.streams.awaitAnyTermination()
> 
> 
> Thanks,
> Aakash.
> 
> On Fri, Apr 6, 2018 at 4:18 PM, Panagiotis Garefalakis <pangaref@gmail.com <mailto:pangaref@gmail.com>>
wrote:
> Hello Aakash,
> 
> When you use query.awaitTermination you are pretty much blocking there waiting for the
current query to stop or throw an exception. In your case the second query will not even start.
> What you could do instead is remove all the blocking calls and use spark.streams.awaitAnyTermination
instead (waiting for either query1 or query2 to terminate). Make sure you do that after the
query2.start call.
> 
> I hope this helps.
> 
> Cheers,
> Panagiotis
> 
> On Fri, Apr 6, 2018 at 11:23 AM, Aakash Basu <aakash.spark.raj@gmail.com <mailto:aakash.spark.raj@gmail.com>>
wrote:
> Any help?
> 
> Need urgent help. Someone please clarify the doubt?
> 
> ---------- Forwarded message ----------
> From: Aakash Basu <aakash.spark.raj@gmail.com <mailto:aakash.spark.raj@gmail.com>>
> Date: Thu, Apr 5, 2018 at 3:18 PM
> Subject: [Structured Streaming] More than 1 streaming in a code
> To: user <user@spark.apache.org <mailto:user@spark.apache.org>>
> 
> 
> Hi,
> 
> If I have more than one writeStream in a code, which operates on the same readStream
data, why does it produce only the first writeStream? I want the second one to be also printed
on the console.
> 
> How to do that?
> 
> from pyspark.sql import SparkSession
> from pyspark.sql.functions import split, col
> 
> class test:
> 
> 
>     spark = SparkSession.builder \
>         .appName("Stream_Col_Oper_Spark") \
>         .getOrCreate()
> 
>     data = spark.readStream.format("kafka") \
>         .option("startingOffsets", "latest") \
>         .option("kafka.bootstrap.servers", "localhost:9092") \
>         .option("subscribe", "test1") \
>         .load()
> 
>     ID = data.select('value') \
>         .withColumn('value', data.value.cast("string")) \
>         .withColumn("Col1", split(col("value"), ",").getItem(0)) \
>         .withColumn("Col2", split(col("value"), ",").getItem(1)) \
>         .drop('value')
> 
>     ID.createOrReplaceTempView("transformed_Stream_DF")
> 
>     df = spark.sql("select avg(col1) as aver from transformed_Stream_DF")
> 
>     df.createOrReplaceTempView("abcd")
> 
>     wordCounts = spark.sql("Select col1, col2, col2/(select aver from abcd) col3 from
transformed_Stream_DF")
> 
> 
>     # -----------------------#
> 
>     query1 = df \
>         .writeStream \
>         .format("console") \
>         .outputMode("complete") \
>         .trigger(processingTime='3 seconds') \
>         .start()
> 
>     query1.awaitTermination()
>     # -----------------------#
> 
>     query2 = wordCounts \
>         .writeStream \
>         .format("console") \
>         .trigger(processingTime='3 seconds') \
>         .start()
> 
>     query2.awaitTermination()
> 
>     # /home/kafka/Downloads/spark-2.3.0-bin-hadoop2.7/bin/spark-submit --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.0,com.databricks:spark-csv_2.10:1.0.3
/home/aakashbasu/PycharmProjects/AllMyRnD/Kafka_Spark/Stream_Col_Oper_Spark.py
> 
> 
> 
> Thanks,
> Aakash.
> 
> 
> 


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