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Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance . Originally developed at the University of California, Berkeley 's AMPLab , the Spark codebase was later donated to the Apache Software Foundation ...
Stream-processing technologies typically used in this layer include Apache Kafka, Amazon Kinesis, Apache Storm, SQLstream, Apache Samza, Apache Spark, Azure Stream Analytics, Apache Flink. Output is typically stored on fast NoSQL databases., [6] [7] or as a commit log. [8]
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.
For example, Apache Tinkerpop [13] forces each node and each edge to have a single label; Cypher allows nodes to have zero to many labels, but relationships only have a single label (called a reltype). Neo4j's database supports undocumented graph-wide properties, Tinkerpop has graph values which play the same role, and also supports ...
As an example, an Apache Spark query may read data from Apache Parquet (column-oriented) load it into Spark internal in-memory format (row-oriented) convert it to Apache Arrow for a specific computation (column-oriented) write it to Apache Avro for streaming (row-oriented)
Holden Karau (born October 4, 1986) is an American-Canadian computer scientist and author based in San Francisco, CA. She is best known for her work on Apache Spark, her advocacy in the open-source software movement, and her creation and maintenance of a variety of related projects including spark-testing-base.
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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.