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Aug 6th, 2022
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How to Join watermark in VIA

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hi welcome back lets talk about water marking we know that in a structured streaming application there is an unbounded input table we perform our processing on top of it using a query and we produce the result in the process spark maintains the state based on the aggregation you perform lets say if you are performing a simple aggregation of a word count your word is say apple and it has come up once orange has come up once after a while lets say after 10 minutes or 20 minutes apple comes up again and your count of apple becomes two so this count has become two because the previous estate was one and apple has come up once again so there is maintenance of the state now the point is how long would you like to maintain the state the longer you maintain the state the higher memory requirement it will have and eventually you need to design a mechanism you need to put a barrier in place that a data which is very old you are not going to process it further now how old the data can be is d

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What is a Watermark? Watermarking is a useful method which helps a Stream Processing Engine to deal with lateness. Basically, a watermark is a threshold to specify how long the system waits for late events. If an arriving event lies within the watermark, it gets used to update a query.
Watermarking is a feature in Spark Structured Streaming that is used to handle the data that arrives late. Spark Structured Streaming can maintain the state of the data that arrives, store it in memory, and update it accurately by aggregating it with the data that arrived late.
Watermarking is a feature in Spark Structured Streaming that is used to handle the data that arrives late. Spark Structured Streaming can maintain the state of the data that arrives, store it in memory, and update it accurately by aggregating it with the data that arrived late.
Watermarks help Spark understand the processing progress based on event time, when to produce windowed aggregates and when to trim the aggregations state. When joining streams of data, Spark, by default, uses a single, global watermark that evicts state based on the minimum event time seen across the input streams.
Watermark is a method to measure the progress of the event time. With event time, every input event has an embedded timestamp. This timestamp can be used for watermarks to indicate the time of incoming events to the operator.
Watermark is a method to measure the progress of the event time. With event time, every input event has an embedded timestamp. This timestamp can be used for watermarks to indicate the time of incoming events to the operator.
For inner joins, Databricks recommends setting a watermark threshold on each streaming data source. This allows state information to be discarded for old records. Without watermarks, Structured Streaming attempts to join every key from both sides of the join with each trigger.
Watermarks are part of the data stream and carry a timestamp t. A Watermark (t) declares that event time has docHubed time t in that stream, meaning that there should be no more elements from the stream with a timestamp t

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