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Showing 21 open source projects for "scala"
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Scio
A Scala API for Apache Beam and Google Cloud Dataflow
Scio is a Scala API developed by Spotify that builds on Apache Beam to enable expressive batch and streaming data pipelines, optimized for running on Google Cloud Dataflow. Inspired by Spark and Scalding, it provides scalable, type‑safe, and production-grade data processing, with built-in support for BigQuery, Pub/Sub, Cassandra, Elasticsearch, Redis, TensorFlow IO, and more. -
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Akka
Build concurrent, distributed, and resilient message-driven apps
Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. ... -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,... -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. ... -
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XGBoost
Scalable and Flexible Gradient Boosting
...XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. 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. -
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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
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AvaSattva
Search replace files or pipe
...And for ETL alike work like Load and filter files -> Extract -> Transform output. For replacing files, you can preview and backup, in multiple directories and files or pipe, with plain text matching or using general Regex as C++, C#, Java, Scala; So msr is a good tool to learn and test Regex since it has different colors for matched groups captured by the Regex pattern. -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features)... -
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Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
...This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created with the Apache Flink framework. You author and build your Apache Flink application locally. Applications primarily use either the DataStream API or the Table API. The other Apache Flink APIs are also available for you to use, but they are less commonly used in building streaming applications. The Apache Flink DataStream API programming model is based on two components. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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SnappyData
Memory optimized analytics database, based on Apache Spark
SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over... -
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rocket-bi
An open-source web-based self-service BI for analytical databases
Rocket.BI is a free, open-source, web-based business intelligence solution specifically designed for analytical databases. It enables data analysts and business users alike to easily integrate different data sources, perform advanced data analysis, ad hoc, and more. With an easy-to-use editor, you can create personalized reports, build interactive business dashboards and generate actionable business insights. Rocket.BI also allows collaboration as working together with other people in the... -
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Semagrams.jl
A graphical editor for graph-like structures
A graphical editor for graph-like structures based on Catlab. Legacy version built with typescript is in the legacy branch, and will not receive updates; new version with scala is now in the main branch. The core of Semagrams is just a library; in order to make it do things, one needs to create an "app" that uses it. Currently, the only app that is being developed is a Petri net editor, though this will soon change. In order to run the Petri net editor standalone, install Mill and npm, and then in one terminal in scala/ run mill --watch apps.petri.fullLinkJS and in another terminal in scala/ run npm run dev. ... -
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SZT-bigdata
SZT‑bigdata is an open source project
SZT‑bigdata is an open-source project analyzing real Shenzhen metro (subway) card usage data using big‑data frameworks like Spark, Hadoop, Hive, Kafka, Flink, ClickHouse, HBase, and Elasticsearch. Aimed at exploring transit passenger flow patterns and system optimization using a variety of Scala-based technologies. -
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DISTOD
Distributed discovery of bidirectional order dependencies
The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books by... -
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to... -
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Cosmos DB Spark
Apache Spark Connector for Azure Cosmos DB
Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data. -
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Waterloo
Java-based scientific graphics
Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab. -
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wspa
Web Scanning Probe Analysis - a web-based tool for SPM data processing
Web Scanning Probe Analysis - a web-based tool for data from SPM (STM, AFM), based on gnudatalanguage. - web-based interface for data management and processing - multiple data formats supported (GXSM, WSXM, Omicron SCALA, Createk) - unified, editable filtering of images, highly versatile -
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Apache Kafka
Mirror of Apache Kafka
Apache Kafka is a distributed streaming platform built around durable, partitioned logs called topics, enabling high-throughput, fault-tolerant event pipelines. Producers append records to partitions, brokers replicate them for durability, and consumer groups read them at their own pace while balancing work across instances. The commit/offset model and retention policies support patterns from real-time processing to event sourcing and audit trails. Exactly-once processing semantics,... -
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Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.
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A basic ray tracer written in the Scala language. Features includes photon mapping and a frontend written in Groovy. Planed features are volumetric lighting and shadow photons.
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