Tensorflow_scala
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Tensorflow_scala | Apache Spark | |
---|---|---|
- | 101 | |
934 | 38,249 | |
- | 1.0% | |
0.0 | 10.0 | |
almost 2 years ago | 6 days ago | |
Scala | Scala | |
Apache License 2.0 | Apache License 2.0 |
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Tensorflow_scala
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Tracking mentions began in Dec 2020.
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?
SynapseML - Simple and Distributed Machine Learning
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Breeze - Breeze is a numerical processing library for Scala.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Smile - Statistical Machine Intelligence & Learning Engine
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
BigDL - Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.
Scalding - A Scala API for Cascading
Spark Notebook - Interactive and Reactive Data Science using Scala and Spark.
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
Squants - The Scala API for Quantities, Units of Measure and Dimensional Analysis
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.