Re: Apache Spark - Spark Structured Streaming - Watermark usage
Hi Jacek: Thanks for your response. I am just trying to understand the fundamentals of watermarking and how it behaves in aggregation vs non-aggregation scenarios. On Tuesday, February 6, 2018 9:04 AM, Jacek Laskowski wrote: Hi, What would you expect? The data is simply dropped as that's the purpose of watermarking it. That's my understanding at least. Pozdrawiam,Jacek Laskowskihttps://about.me/JacekLaskowskiMastering Spark SQL https://bit.ly/mastering-spark-sql Spark Structured Streaming https://bit.ly/spark-structured-streaming Mastering Kafka Streams https://bit.ly/mastering-kafka-streams Follow me at https://twitter.com/jaceklaskowski On Mon, Feb 5, 2018 at 8:11 PM, M Singh wrote: Just checking if anyone has more details on how watermark works in cases where event time is earlier than processing time stamp. On Friday, February 2, 2018 8:47 AM, M Singh wrote: Hi Vishu/Jacek: Thanks for your responses. Jacek - At the moment, the current time for my use case is processing time. Vishnu - Spark documentation (https://spark.apache.org/ docs/latest/structured- streaming-programming-guide. html) does indicate that it can dedup using watermark. So I believe there are more use cases for watermark and that is what I am trying to find. I am hoping that TD can clarify or point me to the documentation. Thanks On Wednesday, January 31, 2018 6:37 AM, Vishnu Viswanath wrote: Hi Mans, Watermark is Spark is used to decide when to clear the state, so if the even it delayed more than when the state is cleared by Spark, then it will be ignored.I recently wrote a blog post on this : http://vishnuviswanath.com/ spark_structured_streaming. html#watermark Yes, this State is applicable for aggregation only. If you are having only a map function and don't want to process it, you could do a filter based on its EventTime field, but I guess you will have to compare it with the processing time since there is no API to access Watermark by the user. -Vishnu On Fri, Jan 26, 2018 at 1:14 PM, M Singh wrote: Hi: I am trying to filter out records which are lagging behind (based on event time) by a certain amount of time. Is the watermark api applicable to this scenario (ie, filtering lagging records) or it is only applicable with aggregation ? I could not get a clear understanding from the documentation which only refers to it's usage with aggregation. Thanks Mans
Re: Apache Spark - Spark Structured Streaming - Watermark usage
Hi, What would you expect? The data is simply dropped as that's the purpose of watermarking it. That's my understanding at least. Pozdrawiam, Jacek Laskowski https://about.me/JacekLaskowski Mastering Spark SQL https://bit.ly/mastering-spark-sql Spark Structured Streaming https://bit.ly/spark-structured-streaming Mastering Kafka Streams https://bit.ly/mastering-kafka-streams Follow me at https://twitter.com/jaceklaskowski On Mon, Feb 5, 2018 at 8:11 PM, M Singh wrote: > Just checking if anyone has more details on how watermark works in cases > where event time is earlier than processing time stamp. > > > On Friday, February 2, 2018 8:47 AM, M Singh wrote: > > > Hi Vishu/Jacek: > > Thanks for your responses. > > Jacek - At the moment, the current time for my use case is processing time. > > Vishnu - Spark documentation (https://spark.apache.org/ > docs/latest/structured-streaming-programming-guide.html) does indicate > that it can dedup using watermark. So I believe there are more use cases > for watermark and that is what I am trying to find. > > I am hoping that TD can clarify or point me to the documentation. > > Thanks > > > On Wednesday, January 31, 2018 6:37 AM, Vishnu Viswanath < > vishnu.viswanat...@gmail.com> wrote: > > > Hi Mans, > > Watermark is Spark is used to decide when to clear the state, so if the > even it delayed more than when the state is cleared by Spark, then it will > be ignored. > I recently wrote a blog post on this : http://vishnuviswanath.com/ > spark_structured_streaming.html#watermark > > Yes, this State is applicable for aggregation only. If you are having only > a map function and don't want to process it, you could do a filter based on > its EventTime field, but I guess you will have to compare it with the > processing time since there is no API to access Watermark by the user. > > -Vishnu > > On Fri, Jan 26, 2018 at 1:14 PM, M Singh > wrote: > > Hi: > > I am trying to filter out records which are lagging behind (based on event > time) by a certain amount of time. > > Is the watermark api applicable to this scenario (ie, filtering lagging > records) or it is only applicable with aggregation ? I could not get a > clear understanding from the documentation which only refers to it's usage > with aggregation. > > Thanks > > Mans > > > > > > >
Re: Apache Spark - Spark Structured Streaming - Watermark usage
Just checking if anyone has more details on how watermark works in cases where event time is earlier than processing time stamp. On Friday, February 2, 2018 8:47 AM, M Singh wrote: Hi Vishu/Jacek: Thanks for your responses. Jacek - At the moment, the current time for my use case is processing time. Vishnu - Spark documentation (https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html) does indicate that it can dedup using watermark. So I believe there are more use cases for watermark and that is what I am trying to find. I am hoping that TD can clarify or point me to the documentation. Thanks On Wednesday, January 31, 2018 6:37 AM, Vishnu Viswanath wrote: Hi Mans, Watermark is Spark is used to decide when to clear the state, so if the even it delayed more than when the state is cleared by Spark, then it will be ignored.I recently wrote a blog post on this : http://vishnuviswanath.com/spark_structured_streaming.html#watermark Yes, this State is applicable for aggregation only. If you are having only a map function and don't want to process it, you could do a filter based on its EventTime field, but I guess you will have to compare it with the processing time since there is no API to access Watermark by the user. -Vishnu On Fri, Jan 26, 2018 at 1:14 PM, M Singh wrote: Hi: I am trying to filter out records which are lagging behind (based on event time) by a certain amount of time. Is the watermark api applicable to this scenario (ie, filtering lagging records) or it is only applicable with aggregation ? I could not get a clear understanding from the documentation which only refers to it's usage with aggregation. Thanks Mans
Re: Apache Spark - Spark Structured Streaming - Watermark usage
Hi Vishu/Jacek: Thanks for your responses. Jacek - At the moment, the current time for my use case is processing time. Vishnu - Spark documentation (https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html) does indicate that it can dedup using watermark. So I believe there are more use cases for watermark and that is what I am trying to find. I am hoping that TD can clarify or point me to the documentation. Thanks On Wednesday, January 31, 2018 6:37 AM, Vishnu Viswanath wrote: Hi Mans, Watermark is Spark is used to decide when to clear the state, so if the even it delayed more than when the state is cleared by Spark, then it will be ignored.I recently wrote a blog post on this : http://vishnuviswanath.com/spark_structured_streaming.html#watermark Yes, this State is applicable for aggregation only. If you are having only a map function and don't want to process it, you could do a filter based on its EventTime field, but I guess you will have to compare it with the processing time since there is no API to access Watermark by the user. -Vishnu On Fri, Jan 26, 2018 at 1:14 PM, M Singh wrote: Hi: I am trying to filter out records which are lagging behind (based on event time) by a certain amount of time. Is the watermark api applicable to this scenario (ie, filtering lagging records) or it is only applicable with aggregation ? I could not get a clear understanding from the documentation which only refers to it's usage with aggregation. Thanks Mans
Re: Apache Spark - Spark Structured Streaming - Watermark usage
Hi Mans, Watermark is Spark is used to decide when to clear the state, so if the even it delayed more than when the state is cleared by Spark, then it will be ignored. I recently wrote a blog post on this : http://vishnuviswanath.com/spark_structured_streaming.html#watermark Yes, this State is applicable for aggregation only. If you are having only a map function and don't want to process it, you could do a filter based on its EventTime field, but I guess you will have to compare it with the processing time since there is no API to access Watermark by the user. -Vishnu On Fri, Jan 26, 2018 at 1:14 PM, M Singh wrote: > Hi: > > I am trying to filter out records which are lagging behind (based on event > time) by a certain amount of time. > > Is the watermark api applicable to this scenario (ie, filtering lagging > records) or it is only applicable with aggregation ? I could not get a > clear understanding from the documentation which only refers to it's usage > with aggregation. > > Thanks > > Mans >
Re: Apache Spark - Spark Structured Streaming - Watermark usage
Hi, I'm curious how would you do the requirement "by a certain amount of time" without a watermark? How would you know what's current and compute the lag? Let's forget about watermark for a moment and see if it pops up as an inevitable feature :) "I am trying to filter out records which are lagging behind (based on event time) by a certain amount of time." Pozdrawiam, Jacek Laskowski https://about.me/JacekLaskowski Mastering Spark SQL https://bit.ly/mastering-spark-sql Spark Structured Streaming https://bit.ly/spark-structured-streaming Mastering Kafka Streams https://bit.ly/mastering-kafka-streams Follow me at https://twitter.com/jaceklaskowski On Fri, Jan 26, 2018 at 7:14 PM, M Singh wrote: > Hi: > > I am trying to filter out records which are lagging behind (based on event > time) by a certain amount of time. > > Is the watermark api applicable to this scenario (ie, filtering lagging > records) or it is only applicable with aggregation ? I could not get a > clear understanding from the documentation which only refers to it's usage > with aggregation. > > Thanks > > Mans >