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This article mainly explains "what are the types of Stream Grouping". The explanation in this article is simple and clear, easy to learn and understand. Please follow the ideas of Xiaobian and go deep into it slowly to study and learn "what are the types of Stream Grouping" together.

Stream Grouping defines how a stream should be split between Bolt tasks. Here are 6 Stream Grouping types provided by Storm:

1. Shuffle grouping: Randomly distribute tuples to Bolt tasks, ensuring that each task receives an equal number of tuples.

2. Fields grouping: Divide and group data streams according to specified fields. For example, tuples of the same "user-id" are always distributed to the same task, and tuples of different "user-ids" may be distributed to different tasks, depending on the "user-id" field.

3. All grouping: Tuple is copied to all tasks of bolt. This type needs to be used with caution.

4. Global grouping: All flows are assigned to the same task of the bolt. Specifically, it is assigned to the task with the smallest ID.

5. None grouping: You don't need to care how streams are grouped. Currently, no grouping is equivalent to randomization. But eventually Storm will put ungrouped Bolts into the same thread to execute (if possible) as Bolts or Spouts subscribe to them.

6. Direct grouping: This is a special grouping type. The tuple producer decides which tuple handler task receives the tuple.

Of course, you can also implement the CustomStreamGroupimg interface to customize the grouping you need.

Thank you for reading, the above is the content of "What are the types of Stream Grouping?" After studying this article, I believe everyone has a deeper understanding of what the types of Stream Grouping are. The specific use situation still needs to be verified by practice. Here is, Xiaobian will push more articles related to knowledge points for everyone, welcome to pay attention!

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