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⛄ After learning some basic Datastream APIs yesterday, let's continue to learn the Table API and SQL on the upper layer of Datastream. Both APIs deal with relational data, which can reduce the development threshold of flink. Students who are interested in the contents of previous periods can refer to the following contents 👇: hadoop topics: ...

Preface: Hudi series: Flinkcdc Hudi: introduction to MySQL data entering the lake in real time 1: preliminary test Flinkcdc Hudi: full introduction to MySQL data entering the lake in real time II: exceptions and solutions encountered during the integration of Hudi and Spark 1, Background In the production environment, mysql is generally eq ...

💦 Today, let's learn about the more basic DataStream API in flink, which is used to process stream data. This article is mainly in the form of pyflink to explain to the small partners who are interested in the content of previous periods 👇: hadoop topics: hadoop series articles.spark topics: spark series.Flynk topics: Flink series. 💛 The A ...

Data preparation The data used below are all the following data sensor_1,1547718199,35.8 sensor_6,1547718201,15.4 sensor_7,1547718202,6.7 sensor_10,1547718205,38.1 sensor_1,1547728199,25.8 sensor_6,1547712201,35.4 sensor_7,1547718102,16.7 sensor_10,1547712205,28.1 Basic conversion operators (Map, FlatMap, Filter) Map map is to tran ...

Last example https://blog.csdn.net/xxkalychen/article/details/117149540?spm=1001.2014.3001.5502 Setting Flink's data source to Socket is just to provide streaming data for testing. This is not generally used in production. The standard model is to obtain streaming data from message queues. Flink provides the encapsulation of connecting with Kaf ...

Flink heavy De duplication calculation should be a common indicator calculation in data analysis business, such as the number of users visiting the website in a day, the number of users clicking on advertisements, etc. offline calculation is a full and one-time calculation process, and the de duplication results can usually be obtained by dist ...

Design ideas In the past, we split the data into independent Kafka topics through diversion and other processing methods. Next, when processing the data, we should consider processing the index items used in real-time calculation. Timeliness is the pursuit of real-time data warehouse. Therefore, in some scenarios, it is not necessary to have a ...

catalogue 0. Links to related articles 1. Introduction to streaming file writing 1.1. Scene description 1.2. Bucket, SubTask and PartFile 2. Case display 2.1. demand 2.2. Development steps 2.3. Implementation code 3. Detailed explanation of streaming file writing configuration 3.1. PartFile 3.1.1. PartFile lifecycle 3.1.2. Gene ...

catalogue 0. Links to related articles 1. Data processing language of stream processing 1.1. At most once 1.2. At least once 1.3. Exactly once 1.4. End to end exactly once 1.5. Accurate once & effective once 1.6. How does stream computing system support consistency semantics 2. Implementation of end to end exactly once 2.1. So ...

Flink built-in trigger and custom window trigger flink: 1.10.1 Github: https://github.com/shirukai/flink-examples-trigger.git Some time ago, colleagues encountered a demand in development, which requires counting according to the 10 minute window of event time. At the same time, when new data is needed, the results are output every min ...