Schemer
Apache Spark
| Schemer | Apache Spark | |
|---|---|---|
| - | 102 | |
| 112 | 38,703 | |
| 0.0% | 0.8% | |
| 0.0 | 10.0 | |
| over 4 years ago | 2 days ago | |
| Scala | Scala | |
| Apache License 2.0 | Apache License 2.0 |
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Schemer
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Tracking mentions began in Dec 2020.
Apache Spark
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Shades of Open Source - Understanding The Many Meanings of "Open"
In contrast, Databricks maintains internal forks of Spark, Delta Lake, and Unity Catalog, using the same names for both the open-source versions and the features specific to the Databricks platform. While they do provide separate documentation, online discussions often reflect confusion about how to use features in the open-source versions that only exist on the Databricks platform. This creates a "muddying of the waters" between what is open and what is proprietary. This isn't an issue if you are a Databricks user, but it can be quite confusing for those who want to use these tools outside of the Databricks ecosystem.
- "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)
What are some alternatives?
Sparkta - Real Time Analytics and Data Pipelines based on Spark Streaming
Trino - Official repository of Trino, the distributed SQL query engine for big data, former
Jupyter Scala - A Scala kernel for Jupyter
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Apache Flink - Apache Flink
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Scoozie - Scala DSL on top of Oozie XML
Scalding - A Scala API for Cascading
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
Summingbird - Streaming MapReduce with Scalding and Storm
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.