Snapshot of apache/flink: 26.4k★, Java, Data. Apache Flink
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Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities.
Learn more about Flink at https://flink.apache.org/
Features
A streaming-first runtime that supports both batch processing and data streaming programs
Elegant and fluent APIs in Java
A runtime that supports very high throughput and low event latency at the same time
Support for event time and out-of-order processing in the DataStream API, based on the Dataflow Model
Flexible windowing (time, count, sessions, custom triggers) across different time semantics (event time, processing time)
Fault-tolerance with exactly-once processing guarantees
Natural back-pressure in streaming programs
Libraries for Graph processing (batch), Machine Learning (batch), and Complex Event Processing (streaming)
Custom memory management for efficient and robust switching between in-memory and out-of-core data processing algorithms
Compatibility layers for Apache Hadoop MapReduce
Integration with YARN, HDFS, HBase, and other components of the Apache Hadoop ecosystem
Streaming Example
// pojo class WordWithCount
public class WordWithCount {
public String word;
public int count;
public WordWithCount() {}
public WordWithCount(String word, int count) {
this.word = word;
this.count = count;
}
}
// main method
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> text = env.socketTextStream(host, port);
DataStream<WordWithCount> windowCounts = text
.flatMap(
(FlatMapFunction<String, String>) (line, collector)
-> Arrays.stream(line.split("\\s")).forEach(collector::collect)
).returns(String.class)
.map(word -> new WordWithCount(word, 1)).returns(TypeInformation.of(WordWithCount.class))
.keyBy(wordWithCnt -> wordWithCnt.word)
.window(TumblingProcessingTimeWindows.of(Duration.ofSeconds(5)))
.sum("count").returns(TypeInformation.of(WordWithCount.class));
windowCounts.print();
env.execute();
}
Batch Example
// pojo class WordWithCount
public class WordWithCount {
public String word;
public int count;
public WordWithCount() {}
public WordWithCount(String word, int count) {
this.word = word;
this.count = count;
}
}
// main method
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setRuntimeMode(RuntimeExecutionMode.BATCH);
FileSource<String> source = FileSource.forRecordStreamFormat(new TextLineInputFormat(), new Path("MyInput.txt")).build();
DataStreamSource<String> text = env.fromSource(source, WatermarkStrategy.noWatermarks(), "MySource");
DataStream<WordWithCount> windowCounts = text
.flatMap((FlatMapFunction<String, String>) (line, collector) -> Arrays
.stream(line.split("\\s"))
.forEach(collector::collect)).returns(String.class)
.map(word -> new WordWithCount(word, 1)).returns(TypeInformation.of(WordWithCount.class))
.keyBy(wordWithCount -> wordWithCount.word)
.sum("count").returns(TypeInformation.of(WordWithCount.class));
windowCounts.print();
env.execute();
Building Apache Flink from Source
Prerequisites for building Flink:
Unix-like environment (we use Linux, Mac OS X, Cygwin, WSL)
Git
Maven (we require version 3.9.16)
Java (version 11, 17, or 21)
Basic Build Instructions
First, clone the repository:
git clone https://github.com/apache/flink.git
cd flink
Then, choose one of the following commands based on your preferred Java version:
Check out our DEVELOPMENT.md guide for detailed IDE setup instructions.
Eclipse Scala IDE
NOTE: From our experience, this setup does not work with Flink
due to deficiencies of the old Eclipse version bundled with Scala IDE 3.0.3 or
due to version incompatibilities with the bundled Scala version in Scala IDE 4.4.1.
We recommend to use IntelliJ instead (see above)
Support
Don’t hesitate to ask!
Contact the developers and community on the mailing lists if you need any help.
Open an issue if you find a bug in Flink.
Documentation
The documentation of Apache Flink is located on the website: https://flink.apache.org
or in the docs/ directory of the source code.
Fork and Contribute
This is an active open-source project. We are always open to people who want to use the system or contribute to it.
Contact us if you are looking for implementation tasks that fit your skills.
This article describes how to contribute to Apache Flink.
Externalized Connectors
Most Flink connectors have been externalized to individual repos under the Apache Software Foundation:
flink-connector-aws
flink-connector-cassandra
flink-connector-elasticsearch
flink-connector-gcp-pubsub
flink-connector-hbase
flink-connector-hive
flink-connector-http
flink-connector-jdbc
flink-connector-kafka
flink-connector-mongodb
flink-connector-opensearch
flink-connector-prometheus
flink-connector-pulsar
flink-connector-rabbitmq
About
Apache Flink is an open source project of The Apache Software Foundation (ASF).
The Apache Flink project originated from the Stratosphere research project.
The most recent commit recorded on apache/flink was 7 days ago, based on the GitHub push timestamp. The repository has 14.1k forks — one of the better signals of community interest.
How many stars does apache/flink have?
apache/flink has 26.4k GitHub stars — refresh the page for the live number, or check github.com/apache/flink. TopGit mirrors GitHub's count but does not claim minute-by-minute accuracy.
What language is apache/flink written in?
apache/flink is written primarily in Java. GitHub's language field is based on the largest share of bytes in the default branch.
What license does apache/flink use?
apache/flink is released under the Apache-2.0 license. Always verify the LICENSE file directly on GitHub for the authoritative terms — license strings can be edited out of sync with a project's actual stance.
What topics is apache/flink associated with?
GitHub's repository topics for apache/flink: "big-data", "flink", "java", "python", "scala", "sql". TopGit's editorial category is Data.
Where can I see apache/flink in action?
The project maintains a homepage at https://flink.apache.org/. The README tab on this page also usually contains screenshots and a quickstart.
Where do I read more about apache/flink?
This TopGit page is a snapshot — the READ ME tab shows the project's own README content (links stripped, images preserved). The GitHub repository at github.com/apache/flink is the definitive source.
Read full README in the tab above.
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