If records are sent faster than they can be The buffer_memory controls the total amount of memory available to the The linger configuration however setting this to something larger than 0Ĭan lead to fewer, more efficient requests when not under maximal load at Records that arrive close together in time will generally batch togetherĮven with linger_ms=0 so under heavy load batching will occur regardless of This is analogous to Nagle’s algorithm in TCP. This will instruct the producer to wait up to that number of millisecondsīefore sending a request in hope that more records will arrive to fill up Number of requests you can set ‘linger_ms’ to something greater than 0. Generally have one of these buffers for each active partition).īy default a buffer is available to send immediately even if there isĪdditional unused space in the buffer. Larger can result in more batching, but requires more memory (since we will Theseīuffers are of a size specified by the ‘batch_size’ config. The producer maintains buffers of unsent records for each partition. Possibility of duplicates (see the documentation on message If the request fails, the producer can automatically retry, unless The record, the slowest but most durable setting. #Get out poducer fullThe “all” setting will result in blocking on the full commit of The ‘acks’ config controls the criteria under which requests are consideredĬomplete. ThisĪllows the producer to batch together individual records for efficiency. Record to a buffer of pending record sends and immediately returns. Thread that is responsible for turning these records into requests and Haven’t yet been transmitted to the server as well as a background I/O The producer consists of a pool of buffer space that holds records that Threads will generally be faster than having multiple instances. The producer is thread safe and sharing a single producer instance across KafkaProducer ( **configs ) ¶Ī Kafka client that publishes records to the Kafka cluster.
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