Search Results for "spark"
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Showing 11 open source projects for "spark"
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1
Synapse Machine Learning
Simple and distributed Machine Learning
...These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. SynapseML also brings new networking capabilities to the Spark Ecosystem. With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster. -
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Deequ
Deequ is a library built on top of Apache Spark
Deequ is a library built atop Apache Spark that enables defining “unit tests for data” — that is, formal constraints or checks on datasets to ensure data quality along dimensions such as completeness, uniqueness, value ranges, correlations, etc. It can scale to large datasets (billions of rows) by translating those data checks into Spark jobs. Deequ supports advanced features like a metrics repository for storing computed statistics over time, anomaly detection of data quality metrics, and the suggestion of likely constraints automatically for new datasets. ... -
3
XGBoost
Scalable and Flexible Gradient Boosting
...It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
4
go-chart
go chart is a basic charting library in go
Package chart is a very simple golang native charting library that supports time-series and continuous line charts. Master should now be on the v3.x codebase, which overhauls the api significantly. Per usual, see examples for more information. Actual chart configurations and examples can be found in the ./examples/ directory. They are simple CLI programs that write to output.png (they are also updated with go generate. Everything on the chart.Chart object has defaults that can be overridden.... -
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5
SageMaker Spark
A Spark library for Amazon SageMaker
SageMaker Spark depends on hadoop-aws-2.8.1. To run Spark applications that depend on SageMaker Spark, you need to build Spark with Hadoop 2.8. However, if you are running Spark applications on EMR, you can use Spark built with Hadoop 2.7. -
6
WTFJS
A list of funny and tricky JavaScript examples
...It’s designed as both a fun read and a serious learning aid, helping developers build an intuition for how JavaScript evaluates expressions. By highlighting common misconceptions, it encourages safer coding patterns and more reliable mental models. Teachers, interviewers, and learners use it to spark discussion and deepen understanding of JavaScript’s semantics. -
7
CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
CoolplaySpark is a learning and practice repository designed to help users understand and work with Apache Spark. It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their understanding of Spark by not only using it as a data processing engine but also exploring how its internals function. ... -
8
osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
9
PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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10
benchm-ml
A benchmark of commonly used open source implementations
...The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
11
Dynamic Flex forms
Components to generate a flex (spark) form dynamically
Proof of concept project to investigate the potential to generate Flex forms from a dynamic (possibly externalised) source to cut development time building common form functionality. I've previously used 'control' classes to allow non technical users to configure form validation parameters in an external XML file, however the form & model still required development time. As an extension of the form class to function more like a SkinnableDataComponent the form items become...
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