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Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.
A fourth version of the SPARK language, SPARK 2014, based on Ada 2012, was released on April 30, 2014. SPARK 2014 is a complete re-design of the language and supporting verification tools. The SPARK language consists of a well-defined subset of the Ada language that uses contracts to describe the specification of components in a form that is ...
Apache SystemDS (Previously, Apache SystemML) is an open source ML system for the end-to-end data science lifecycle. SystemDS's distinguishing characteristics are: Algorithm customizability via R-like and Python-like languages. Multiple execution modes, including Standalone, Spark Batch, Spark MLContext, Hadoop Batch, and JMLC.
HBase: Apache HBase software is the Hadoop database. Think of it as a distributed, scalable, big data store; Helix: a cluster management framework for partitioned and replicated distributed resources; Hive: the Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
Apache Iceberg is a high performance open-source format for large analytic tables. Iceberg enables the use of SQL tables for big data while making it possible for engines like Spark , Trino , Flink , Presto , Hive , Impala , StarRocks, Doris, and Pig to safely work with the same tables, at the same time. [ 1 ]
Data version control is a method of working with data sets. It is similar to the version control systems used in traditional software development, but is optimized to allow better processing of data and collaboration in the context of data analytics, research, and any other form of data analysis.
Apache License, Version 2.0: mod_setenvifplus: Version 2.2 and newer: Third-party module: Pascal Buchbinder: Apache License, Version 2.0: Allows Apache to set environment variables based on different parts of a request parsed by regular expressions and encode/decode Base64. [104] mod_so: Version 1.3 and newer: Stable Extension: Apache Software ...