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The editor will share with you what apache flink refers to. I hope you will gain a lot after reading this article. Let's discuss it together.

Apache Flink is an open source stream processing framework developed by the Apache Software Foundation. Its core is a distributed stream data stream engine written in Java and Scala. Flink executes arbitrary streaming data programs in data parallelism and pipelining, and the pipelined runtime system of Flink can execute batch and streaming programs. In addition, the Flink runtime itself supports the execution of iterative algorithms.

Flink provides a high-throughput, low-latency streaming data engine and support for event-time processing and state management. Flink applications are fault tolerant in the event of machine failures and support exactly-once semantics. Programs can be written in languages such as Java, Scala [9], Python [and SQL], and are automatically compiled and optimized to data flow programs that run in a cluster or cloud environment.

Flink does not provide its own data storage system, but provides data sources and receivers for systems such as Amazon Kinesis, Apache Kafka, HDFS, Apache Cassandra, and ElasticSearch.

Apache Flink's data flow programming model provides single event (event-at-a-time) processing on finite and infinite datasets. At the basic level, the Flink program consists of streams and transformations. Conceptually, a stream is a (possibly endless) data flow record, and a transformation is an operation that takes one or more streams as input and thus produces one or more output streams.

Apache Flink includes two core API: data flow API for bounded or unbounded data streams and dataset API for bounded datasets. Flink also provides a table API, an expression language similar to SQL for relational flows and batches that can be easily embedded in Flink's data streams and dataset API. The highest-level language supported by Flink is SQL, which is semantically similar to the table API and represents the program as an SQL query expression.

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