Apache Flink
Apache Kafka
Our great sponsors
Apache Flink | Apache Kafka | |
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9 | 26 | |
23,128 | 27,275 | |
1.0% | 1.1% | |
9.9 | 9.9 | |
about 12 hours ago | about 8 hours ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Apache Flink
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First 15 Open Source Advent projects
7. Apache Flink | Github | tutorial
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Pyflink : Flink DataStream (KafkaSource) API to consume from Kafka
Does anyone have fully running Pyflink code snippet to read from Kafka using the new Flink DataStream (KafkaSource) API and just print out the output to console or write it out to a file. Most of the examples and the official Flink GitHubare using the old API (FlinkKafkaConsumer).
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I keep getting build failure when I try to run mvn clean compile package
I'm trying to use https://github.com/mauricioaniche/ck to analyze the ck metrics of https://github.com/apache/flink. I have the latest version of java downloaded and I have the latest version of apache maven downloaded too. My environment variables are set correctly. I'm in the correct directory as well. However, when I run mvn clean compile package in powershell it always says build error. I've tried looking up the errors but there's so many. https://imgur.com/a/Zk8Snsa I'm very new to programming in general so any suggestions would be appreciated.
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How do I determine what the dependencies are when I make pom.xml file?
Looking at the project on github, it seems like they should have a pom in the root dir https://github.com/apache/flink/blob/master/pom.xml
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Akka is moving away from Open Source
Akka is used only as a possible RPC implementation, isn't it?
- We Are Changing the License for Akka
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Apache Drill, Druid, Flink, Hive, Kafka, Spark
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Computation reuse via fusion in Amazon Athena
It took me some time to get a good grasp of the power of SQL; and it really kicked in when I learned about optimization rules. It's a program that you rewrite, just like an optimizing compiler would.
You state what you want; you have different ways to fetch and match and massage data; and you can search through this space to produce a physical plan. Hopefully you used knowledge to weight parts to be optimized (table statistics, like Java's JIT would detect hot spots).
I find it fascinating to peer through database code to see what is going on. Lately, there's been new advances towards streaming databases, which bring a whole new design space. For example, now you have latency of individual new rows to optimize for, as opposed to batch it whole to optimize the latency of a dataset. Batch scanning will be benefit from better use of your CPU caches.
And maybe you could have a hybrid system which reads history from a log and aggregates in a batched manner, and then switches to another execution plan when it reaches the end of the log.
If you want to have a peek at that here are Flink's set of rules [1], generic and stream-specific ones. The names can be cryptic, but usually give a good sense of what is going on. For example: PushFilterIntoTableSourceScanRule makes the WHERE clause apply the earliest possible, to save some CPU/network bandwidth further down. PushPartitionIntoTableSourceScanRule tries to make a fan-out/shuffle happen the earliest possible, so that parallelism can be made use of.
[1] https://github.com/apache/flink/blob/5f8fb304fb5d68cdb0b3e3c...
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Avro SpecificRecord File Sink using apache flink is not compiling due to error incompatible types: FileSink<?> cannot be converted to SinkFunction<?>
[1]: https://mvnrepository.com/artifact/org.apache.avro/avro-maven-plugin/1.8.2 [2]: https://github.com/apache/flink/blob/master/flink-connectors/flink-connector-files/src/main/java/org/apache/flink/connector/file/sink/FileSink.java [3]: https://ci.apache.org/projects/flink/flink-docs-master/docs/connectors/datastream/file_sink/ [4]: https://github.com/apache/flink/blob/c81b831d5fe08d328251d91f4f255b1508a9feb4/flink-end-to-end-tests/flink-file-sink-test/src/main/java/FileSinkProgram.java [5]: https://github.com/rajcspsg/streaming-file-sink-demo
Apache Kafka
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On Implementation of Distributed Protocols
Apache Kafka — a distributed event streaming platform implementing a variant of the Raft consensus protocol (written in Java, integrated with Scala);
- Implementing tagged fields for Kafka Protocol
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Help me identify this design pattern
Spring does this during autoconfiguration. For example this and this. When the user adds a configuration then it gets to overwrite the default from the template. I am looking for something similar, perhaps simpler approach.
- Kafka Broker Config properties
- Scala DevInTraining looking to contribute to projects
- *bip*
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What is Kafka ?
Source and documentation on GitHub
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A simple file source/sink connector?
Code is still in trunk though. https://github.com/apache/kafka/tree/trunk/connect/file/src/main/java/org/apache/kafka/connect/file
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Can someone please eli5 how the hierarchical timing wheel algorithm works?
I briefly described the algorithm in this article and there is a wonderful article from Kafka that goes into more depth in their general purpose implementation. My implementation is specialized and over optimized in comparison, e.g. by using bit manipulation to avoid more expensive division/modulus instructions. Tokio rewrote their timerwheel after I showed them mine, borrowing some ideas but also staying more general. Hope that helps!
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How-to-Guide: Contributing to Open Source
Apache Kafka
What are some alternatives?
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
celery - Distributed Task Queue (development branch)
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
Apache ActiveMQ Artemis - Mirror of Apache ActiveMQ Artemis
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
H2O - Sparkling Water provides H2O functionality inside Spark cluster
jetstream - JetStream Utilities
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
Aeron - Efficient reliable UDP unicast, UDP multicast, and IPC message transport
Gearpump - Lightweight real-time big data streaming engine over Akka
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.