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Enriching Streams with Hive tables via Flink SQL

Cloudera

Stream processing is about creating business value by applying logic to your data while it is in motion. Many times that involves combining data sources to enrich a data stream. Flink SQL does this and directs the results of whatever functions you apply to the data into a sink. A sink for writing Flink results.

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What is new in Cloudera Streaming Analytics 1.4?

Cloudera

At the end of March, we released the first version of Cloudera SQL StreamBuilder as part of CSA 1.3. It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. . Flink SQL DDL and Catalog support. Improved Table Management.

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Cloudera Streaming Analytics 1.4: the unification of SQL batch and streaming

Cloudera

In October of 2020 Cloudera acquired Eventador and Cloudera Streaming Analytics (CSA) 1.3.0 It was the first release to incorporate SQL Stream Builder (SSB) from the acquisition, and brought rich SQL processing to the already robust Apache Flink offering. Why batch + streaming? A bit of Flink history.

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What is new in Cloudera Streaming Analytics 1.5?

Cloudera

At the end of May, we released the second version of Cloudera SQL Stream Builder (SSB) as part of Cloudera Streaming Analytics (CSA). Since then, we have added a RESTful API as a first class citizen to SSB, doubled down on Flink SQL for defining all aspects of SQL jobs, and upgraded to Apache Flink 1.13.

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