apache flink example

://localhost:8081/jobs{"jobs-running":[],"jobs-finished":["f91d4dd4fdf99313d849c9c4d29f8977"],"jobs-cancelled":[],"jobs-failed":[]} 3. Query for a specified JOB information:/jobs/jobid. The results of this query will return very much more detailed content, which I have tested in the browser, such as:Figure 9. Rest queries for specific JOB informationReaders who want to learn more about Rest requests can go to the Apache

How to combine Flink Table and SQL with Apache CalciteWhat is Apache Calcite? Apache Calcite is designed for Hadoop's new SQL engine. It provides standard SQL languages, multiple query optimizations, and the ability to connect to various data sources. In addition, Calcite also provides a query engine for OLAP and strea

Https://www.iteblog.com/archives/1624.html Whether we need another new data processing engine. I was very skeptical when I first heard of Flink. In the Big data field, there is no shortage of data processing frameworks, but no framework can fully meet the different processing requirements. Since the advent of Apache Spark, it seems to have become the best framework for solving most of the problems today, s

The following document is translated this morning, because to work, time is rather hasty, some parts did not translate, please forgive me.June 01, 2017 the Apache Flink community officially released the 1.3.0 version. This release underwent four months of development and resolved 680 issues. Apache Flink 1.3.0 is the f

). Therefore, if you use persistence as a savepoint as a filesystem jobmanager checkpoint, Flink will not be implemented in this case fault tolerance because the job manager checkpoint data will not be accessible after the reboot. Therefore, it is best to ensure the consistency of two mechanisms.Flink SavepointStoreFactory#createFromConfig creates a specific implementation by combining the configuration file StateStore .SummaryIn this paper, we mainly

正运行到时候才知道是哪个子类，这样就不能提前做优化； 实际测，性能的差距在2.7倍左右 解决方法：Approach 1:make sure that only one memory segment implementation is ever loaded.We re-structured The code a bit to make sure this all places that produce long-lived and short-lived memory segments Insta Ntiate the same memorysegment subclass (Heap-or off-heap segment). Using factories rather than directly instantiating the memory segment classes, this is straightforward. 如果在代码里面只可能实例化其中的一个子类，另一个子类根本就没有被实例化过，那么JIT会意识到，并做优化；我们可以用factories来实例化对象，这样更方

types of data processing modelsMainly divided into two categories, ①streaming, Flow-type, in the data constantly generated at the same time continue to process data ②batch, batch, in a limited time to complete a batch of data processing, after processing the end of the release of computing resourcesAlthough the effects of a non-matching pairing may not be satisfactory, it is true that you can use any data processing model to process any type of dataset, for

the method are called, the final result is to return an outcome to determine the behavior that occurs after the trigger (for example, to call the window function or discard the Windows), which is expressed by the definition trigger trigger behavior TriggerResult . It is an enumeration type with so many enumerated values: The Fire:window will be evaluated using the window function and then emit the result, but the element is not cleaned and s

This article is published by NetEase Cloud.This article is connected with an Apache flow framework Flink,spark streaming,storm comparative analysis (Part I)2.Spark Streaming architecture and feature analysis2.1 Basic ArchitectureBased on the spark streaming architecture of Spark core.Spark streaming is the decomposition of streaming calculations into a series of short batch jobs. The batch engine here is s

This article is a summary of the Flink fault tolerance . Although there are some details that are not covered, the basic implementation points have been mentioned in this series.Reviewing this series, each article involves at least one point of knowledge. Let's sum it up in a minute.Recovery mechanism implementationThe objects in Flink that normally require state recovery are operator as well function . The

the distributed runtime of Apache FlinkTasks and Operator ChainsWhen distributed execution, Flink can link operator subtasks to tasks, each task is executed by one thread, which is an effective optimization, avoids the overhead of thread switching and buffering, improves the overall throughput under the premise of reducing delay, and the link behavior can be configuredJob managers,task Managers and clientsT

to determine whether it is the result of a Job successful return or a failed return.SummaryAt this point, the key method call path of the client submission streaming job has been combed through. In order to highlight the main route and avoid being disturbed by too much implementation detail, we temporarily overlook the interpretation of some important data structures and key concepts. However, we will analyze them later on. Scan code Attention public number: Apache_flink

Apache is a streaming framework that officially provides Docker mirroring, and also provides instructions based on the Docker-compose runDocker-compose fileversion: "2.1"services: jobmanager: image: flink expose: - "6123" ports: - "8081:8081" command: jobmanager environment: - JOB_MANAGER_RPC_ADDRESS=jobmanager taskmanager: image: flin