avaje-jex
Apache Spark
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avaje-jex | Apache Spark | |
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3 | 101 | |
19 | 38,320 | |
- | 1.1% | |
4.7 | 10.0 | |
6 months ago | 6 days ago | |
Java | Scala | |
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.
avaje-jex
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Libraries other than Spring Boot for creating web APIs
I created https://github.com/avaje/avaje-jex ... with the hope of helping to move Javalin more in the Java direction but yeah, Javalin isn't going in that direction. So avaje-jex now will follow it's own path (as pretty much a web routing layer that abstracts over various http servers like jetty, grizzly etc with a java and loom focus).
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is anyone want to join maintaining spark java framework?
Well, ultimately I instead ended up creating jex - https://github.com/avaje/avaje-jex
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Practical intro into creating Virtual Threads with project Loom
The Jetty ones use Jex and Loom based Jetty ThreadPool implementation ... and note that this isn't how the Jetty folks themselves have been playing around with Loom (see their loom branch). However, testing this just now against the latest 19 EA in what I think is the worst case scenario for Loom has: Loom at 80 rps and Traditional at 90 rps. Worse case scenario for loom meaning there is NO WAIT AT ALL in the response and that we do not exceed the Traditional Jetty thread pool size (testing at 100 concurrent clients which is less than default 200 max Jetty thread pool). As soon as we introduce IO wait + exceed the traditional thread pool size in terms of concurrent activity is when we see loom win out.
Apache Spark
- "xAI will open source Grok"
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Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉.
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🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
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Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
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Five Apache projects you probably didn't know about
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features.
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Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Integrate Pyspark Structured Streaming with confluent-kafka
Apache Spark - https://spark.apache.org/
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Spark – A micro framework for creating web applications in Kotlin and Java
A JVM based framework named "Spark", when https://spark.apache.org exists?
- Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
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PySpark SparkSession Builder with Kubernetes Master
I recently saw a pull request that was merged to the Apache/Spark repository that apparently adds initial Python bindings for PySpark on K8s. I posted a comment to the PR asking a question about how to use spark-on-k8s in a Python Jupyter notebook, and was told to ask my question here.
What are some alternatives?
test-driven-learning - Learning tests
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
RESTEasy - An Implementation of the Jakarta RESTful Web Services Specification
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
rest - Jakarta RESTful Web Services
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
manifold - Manifold is a Java compiler plugin, its features include Metaprogramming, Properties, Extension Methods, Operator Overloading, Templates, a Preprocessor, and more.
Scalding - A Scala API for Cascading
airlift - Airlift framework for building REST services
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
Netty - Netty project - an event-driven asynchronous network application framework
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.