You could do it if you had a timestamp in your data. You can use windowed operations to divide a value by it’s own average over a window. However, in structured streaming, you can only window by timestamp columns. You cannot do windows aggregations on integers.
From: Aakash Basu <aakash.spark....@gmail.com> Date: Monday, April 16, 2018 at 4:52 AM To: "Lalwani, Jayesh" <jayesh.lalw...@capitalone.com> Cc: spark receiver <spark.recei...@gmail.com>, Panagiotis Garefalakis <panga...@gmail.com>, user <user@spark.apache.org> Subject: Re: [Structured Streaming] More than 1 streaming in a code Hey Jayesh and Others, Is there then, any other way to come to a solution for this use-case? Thanks, Aakash. On Mon, Apr 16, 2018 at 8:11 AM, Lalwani, Jayesh <jayesh.lalw...@capitalone.com<mailto:jayesh.lalw...@capitalone.com>> wrote: Note that what you are trying to do here is join a streaming data frame with an aggregated streaming data frame. As per the documentation, joining an aggregated streaming data frame with another streaming data frame is not supported From: spark receiver <spark.recei...@gmail.com<mailto:spark.recei...@gmail.com>> Date: Friday, April 13, 2018 at 11:49 PM To: Aakash Basu <aakash.spark....@gmail.com<mailto:aakash.spark....@gmail.com>> Cc: Panagiotis Garefalakis <panga...@gmail.com<mailto:panga...@gmail.com>>, user <user@spark.apache.org<mailto:user@spark.apache.org>> Subject: Re: [Structured Streaming] More than 1 streaming in a code 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....@gmail.com<mailto:aakash.spark....@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 <panga...@gmail.com<mailto:panga...@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....@gmail.com<mailto:aakash.spark....@gmail.com>> wrote: Any help? Need urgent help. Someone please clarify the doubt? ---------- Forwarded message ---------- From: Aakash Basu <aakash.spark....@gmail.com<mailto:aakash.spark....@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. ________________________________ The information contained in this e-mail is confidential and/or proprietary to Capital One and/or its affiliates and may only be used solely in performance of work or services for Capital One. 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