PHP implements open source Flink real-time computing

With the advent of the big data era, the continuous updating and improvement of large-scale real-time data processing methods has attracted much attention and importance. With the continuous development of cloud computing and container technology, Apache Flink has become a real-time computing engine that quickly processes streaming data (such as an algorithm between Spark and Storm) and also provides batch processing support.

Flink is an event-driven processing engine that supports unbounded and bounded data stream processing. It not only has advantages in speed and throughput of stream processing, but also has been widely used in complex event analysis, machine learning, graphics processing and analysis, etc.

This article will introduce how to use PHP language to implement Flink real-time computing.

1. Install Flink

Flink requires Java JDK 8 or higher to run. Before installing, make sure you have Java JDK installed. Let's install Flink below:

1. Download the Apache Flink binary compression package

Go to the Flink official website to download Flink and select the latest Flink 1.14.0 version. You can also use the following command to download:

$ wget https://archive.apache.org/dist/flink/flink-1.14.0/flink-1.14.0-bin-scala_2.11.tgz

2. Decompress the installation package

Use the following command to decompress the downloaded Flink installation package:

$ tar -xvzf flink-1.14.0-bin-scala_2.11.tgz

3. Start the Flink cluster

Use the following command to start the Flink cluster:

$ cd flink-1.14.0/bin/
$ ./start-cluster.sh

Use the following command to check whether the Flink cluster is started:

$ ./flink list

2. PHP implements Flink real-time computing

Before this, you need to understand how Flink processes data. Flink uses the DataStream API to handle data streams. Users can use the DataStream API to build data stream processing applications.

Below we will use the PHP language to implement the Flink data stream processing application.

1. Write PHP code

Use the following code to generate a simple data stream:

require_once 'vendor/autoload.php';

use FlinkDataStream;

$env = new FlinkEnvironment();

$stream = $env->fromCollection([
    [1, 'apple'],
    [2, 'banana'],
    [3, 'cherry']
]);

$stream->print();

Use the following command to execute the PHP code:

$ php myDataStream.php

The output results are as follows:

1, apple
2, banana
3, cherry

2. Create Flink job

Flink job is composed of Flink’s DataSource (data source) and DataSink (data sink).

In the DataStream API, the DataSource is created by the method of the StreamExecutionEnvironment class and can obtain data from an in-memory collection, a file system, or a data source such as Kafka.

Use the following code to write the data in the DataStream to a text file:

require_once 'vendor/autoload.php';

use FlinkEnvironment;
use FlinkDataStreamStreamExecutionEnvironment;

$env = new Environment();
$stream = $env->fromCollection([
    [1, 'apple'],
    [2, 'banana'],
    [3, 'cherry']
]);

$stream->writeAsCsv('/path/to/file.csv');

$env->execute();

After executing the above code, a file named file.csv will be generated under the specified path, and The data of DataStream is written into this file, and the content is as follows:

1,apple
2,banana
3,cherry

3. Conclusion

This article introduces how to use PHP language to implement Flink real-time computing. We installed Flink, wrote a simple data flow using PHP code, and wrote it to a text file. Flink provides a powerful Event Processing Engine and DataStream API that can be used to process real-time data streams. Flink has advantages in speed and throughput of real-time computing, and is increasingly used in machine learning, graphics processing, and analysis.

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