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99 ways to enrich streaming data with Apache Flink


Description

Objective: learning the different ways to enrich a data stream in Apache Flink. The data enrichment is probably a fundamental element in streaming but also a tricky one. Indeed, as in a stream, we have a golden rule to respect: NEVER BLOCKING CALL. But a JDBC connection and requests are typically blocking… so how can we do that?

Content
  • Introduction
  • Is It Enrichment ?
  • Per record synchronous data lookup
  • Per record synchronous lookup
  • Per record asynchronous data lookup Asynch
  • Asynchronous Data Lookup
  • Closer look at the asynchInvoke function
  • In memory cache
  • In memory cache
  • Reference data pre-loading
  • Pre loading
  • Partitioned reference data pre loading
  • Partitioned reference data pre loading
  • Periodic Partitioned data loading
  • Periodic Partitioned data loading
  • Pre loading cache
  • Pre loading cache
  • Reference data change Stream
  • Reference data change Stream
  • Reference data change Stream
  • Simple Event time join
  • Simple Event time join
  • Temporal Table join
  • test_1598865720
  • Summary
Completion rules
  • All units must be completed
  • Leads to a certificate with a duration: Forever
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