streamparse
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streamparse | Apache Spark | |
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1 | 101 | |
1,490 | 38,320 | |
0.1% | 1.1% | |
0.0 | 10.0 | |
8 months ago | 3 days ago | |
Python | Scala | |
Apache License 2.0 | Apache License 2.0 |
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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.
streamparse
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Apache Heron: A realtime, distributed, fault-tolerant stream processing engine
Wonder why this is getting posted today in particular?
The quick summary here is that this was a clean-house rewrite of Apache Storm done by an internal team at Twitter. As an open source project history refresher, Apache Storm was originally built by a startup called Backtype, and the project was led by Nathan Marz, the technical founder of Backtype. Then, Backtype was acquired by Twitter, and Storm became a major component for large-scale stream processing (of tweets, tweet analytics, and other things) at Twitter.
I wrote a summary of the "interesting bits" of Apache Storm here:
https://blog.parse.ly/storm/
However, at a certain point, Nathan Marz left Twitter, and a different group of engineers tried to rethink Storm inside Twitter. There was also a lot of work going on around Apache Mesos at the time. Heron is kind of a merger of their "rethinking" of Storm while also making it possible to manage Storm-like Heron clusters using Mesos.
But, I don't think Heron really took off. Meanwhile, Storm got very, very stable in the 1.x series, and then had a clean-house rewrite from Clojure to Java in the 2.x series. The last stable/major Storm release was in 2020.
Storm provides a stream processing programming API, a multi-lang wire protocol, and a cluster management approach. But certain cluster computing problems can probably be better solved at the infrastructure layer today. That said, it's still a very powerful system; on my team, we process 75K+ events per second across hundreds of vCPU cores and thousands of Python processes by combining Storm and Kafka with our open source project, streamparse.
https://github.com/Parsely/streamparse
(Also, I'd be remiss if I didn't mention -- if you're interested in stream processing and distributed computing, we are hiring Python Data Engineers to work on a stack involving Storm, Spark, Kafka, Cassandra, etc.) -- https://www.parse.ly/careers/python_data_engineer
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.