Configuration # By default, the Table & SQL API is preconfigured for producing accurate results with acceptable performance. Depending on the requirements of a table program, it might be necessary to adjust certain parameters for optimization. For example, unbounded streaming programs may need to ensure that the required state size is capped (see streaming concepts). Overview # When instantiating a TableEnvironment, EnvironmentSettings can be used to pass the desired configuration for the cur...| nightlies.apache.org
Versioned Tables # Flink SQL operates over dynamic tables that evolve, which may either be append-only or updating. Versioned tables represent a special type of updating table that remembers the past values for each key. Concept # Dynamic tables define relations over time. Often, particularly when working with metadata, a key’s old value does not become irrelevant when it changes. Flink SQL can define versioned tables over any dynamic table with a PRIMARY KEY constraint and time attribute.| nightlies.apache.org
Time Attributes # Flink can process data based on different notions of time. Processing time refers to the machine’s system time (also known as epoch time, e.g. Java’s System.currentTimeMillis()) that is executing the respective operation. Event time refers to the processing of streaming data based on timestamps that are attached to each row. The timestamps can encode when an event happened. For more information about time handling in Flink, see the introduction about event time and water...| nightlies.apache.org
Dynamic Tables # SQL - and the Table API - offer flexible and powerful capabilities for real-time data processing. This page describes how relational concepts elegantly translate to streaming, allowing Flink to achieve the same semantics on unbounded streams. Relational Queries on Data Streams # The following table compares traditional relational algebra and stream processing for input data, execution, and output results. Relational Algebra / SQL Stream Processing Relations (or tables) are bo...| nightlies.apache.org
Joins # Batch Streaming Flink SQL supports complex and flexible join operations over dynamic tables. There are several different types of joins to account for the wide variety of semantics queries may require. By default, the order of joins is not optimized. Tables are joined in the order in which they are specified in the FROM clause. You can tweak the performance of your join queries, by listing the tables with the lowest update frequency first and the tables with the highest update frequen...| nightlies.apache.org