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A brief analysis of spark design idea

Spark is no rocket science!—— bloggerKnowing a friend of distributed computing, you must know a concept like dag. I actually contacted the Dag and learned about MapReduce. (See the " Big Data Day: Architecture and Algorithms " book for more details.) Recommended reading. )DAG, directed acyclic graph. Can be a brain to complement what the DAG is a thing: the direction, no ring, the figure, if only, meaning is really clear. If the DAG is more complex, i

11.Spark Streaming source code interpretation of the driver Receivertracker architecture design and concrete implementation of the thorough research

streamidtounallocatedblockqueues, and the Streamid and block queues are encapsulated as allocatedblocks, and finally according to the batchtime the corresponding allocatedblocks objects are added to the timetoallocatedblocks,Timetoallocatedblocks is a hashmap:This allows the block of batch to be allocated for completion. other messages processed by 2.3 receivertrackerin Receivertrackerthe Receivertrackerendpoint Receive method defines the processing logic for various messages:(1) after receivi

Spark Streaming source code interpretation of driver Receivertracker architecture design with concrete implementation of thorough research

information, but as an internal management objectIf you speak from a design pattern, receivertracker and receiverblocktracker, or our RPC communication objects and receiverblocktracker their design patterns are façade (Facet) Design Patterns:Receiverblocktracker: doing things insideReceivertracker: An external communication body or representative.   Note:

Spark Architecture Design & Programming Model 02

Start Spark-shell:Simple RDD:The above code uses the SC, which is Spark-shell help us to automatically generate an instance of Sparkcontext:We multiply each element of the generated RDD by 3:All of the above actions are transformations we need to trigger an action to execute:We can see the expected results, but we can see that the collect operation returns an array, so the data is not too much, or oom will

11th Lesson: Spark Streaming the Receivertracker architecture design and concrete implementation of driver in source code interpretation

maximum ingestion rate */def sendrateupdate (Streamuid:int, newrate:long): Unit = synchronized { if (istrackerstarted) {endpoint.send (Updatereceiverratelimit (Streamuid, Newrate))}}Case Updatereceiverratelimit (Streamuid, newrate) + = (Info The rate at which the data flow is controlled is finally adjusted by Blockgenerator to adjust the rate at which the message is sent to Receiver,receiver.Case Updateratelimit (EPS) = Loginfo (S "Received a new rate limit: $eps.") Registeredblockgenerators.fo

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