Search Results for "open personal data"

Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming...

Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as...

Graphcool was an open-source framework for developing and deploying GraphQL-based backends. It acts as a “backend-as-a-service / framework” that lets you define your data model via GraphQL SDL (Schema Definition Language), and in turn generates a GraphQL CRUD API, supports nested mutations, filtering, pagination, and real-time subscriptions. Graphcool separates the business logic from stateful storage components, allowing the stateful parts (database, subscription engine) to scale independently and giving flexibility in how you compose your system. ...

Scalding is a Scala DSL built on Cascading that simplifies writing Hadoop MapReduce jobs. It lets users describe data transformations using Scala’s functional abstractions, while abstracting away low-level Hadoop boilerplate. It enables expressive and testable pipeline definitions and integrates with various input/output formats.

Summingbird is a streaming + batch hybrid computation framework developed by Twitter. Its aim is to let developers express data aggregation pipelines in a unified way, where the same logic can run either in real time (stream) or in batch mode, and the results can be merged or reconciled. In effect, Summingbird abstracts over multiple execution engines (such as Storm, Scalding, etc.) to provide one high-level program that composes transformations and aggregations, and then executes them in...

Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.

Gizzard is a Scala framework originally developed by Twitter for building scalable, fault-tolerant, distributed key-value stores that can be sharded and replicated. It provides infrastructure for routing requests through shard trees, splitting or rebalancing shards dynamically, failover, and migrations. In Gizzard, data is stored in underlying storage shards (which could be databases or other stores) and Gizzard handles the process of routing requests correctly as the cluster topology...

IMPORTANT: This project is no longer maintained. All the effort is targeted on project Radargun: http://radargun.sourceforge.net

Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.