How to implement real-time data processing using PHP and Kafka

In recent years, the demand for real-time data processing has continued to grow. Cold start and batch-based technologies can no longer meet the needs of real-time data processing. Therefore, more companies are turning to real-time data processing technology. This article will introduce how to use PHP and Kafka to achieve real-time data processing.

Kafka is a high-throughput distributed stream processing platform originally developed by LinkedIn. Kafka can be used to create new stream processing, batch processing, messaging systems, coordination systems, etc.

PHP is a popular dynamic programming language that is widely used to build Internet applications. Although PHP is not the first choice for real-time data processing, it is widely used in web development and data processing.

Now we will introduce the steps on how to use PHP and Kafka to achieve real-time data processing.

Step One: Install and Configure PHP

Before starting real-time data processing with PHP, we need to install the PHP environment and add necessary PHP extensions, such as Kafka extensions and Redis extensions.

Kafka extension can be downloaded and installed from this link kafka, pecl install kafka install kafka extension.

Redis extension You can download and install the PHP Redis extension from here, or you can use PECL to install it, command: pecl install redis.

After installing and configuring the PHP extension, we can start writing real-time data processing programs.

Step 2: Connect to Kafka

Use Kafka producers and Kafka consumers to connect data streams in Kafka in order to transmit data to the "data pipeline". In PHP, we can use the KafkaProducer and KafkaConsumer classes provided by Kafka and instantiate them to connect to Kafka.

The sample code is as follows:

<?php

$kafkaConf = new RdKafkaConf();
$kafkaConf->set('metadata.broker.list', 'localhost:9092');//设置kafka连接信息
$kafkaProducer = new RdKafkaProducer($kafkaConf);
$kafkaConsumer = new RdKafkaConsumer($kafkaConf);
$topic = $kafkaProducer->newTopic('sample');

?>

Step 3: Data reading

We can use the KafkaConsumer class to obtain real-time data streams. In Kafka, there is the concept of a stream, which divides the data flow into one or more partitions, each partition consists of a master partition and zero or more slave partitions. In PHP, we can use the KafkaConsumer class to instantiate a consumer object and subscribe to one or more partitions to read data.

The sample code is as follows:

<?php

$kafkaConf = new RdKafkaConf();
$kafkaConf->set('metadata.broker.list', 'localhost:9092');//设置kafka连接信息
$kafkaConsumer = new RdKafkaConsumer($kafkaConf);

$topicConf = new RdKafkaTopicConf();
$topicConf->set('auto.offset.reset', 'smallest');

$topic = $kafkaConsumer->newTopic('sample', $topicConf);

var_dump($topic->getMetadata(true, 10000));

$topic->consumeStart(0, RD_KAFKA_OFFSET_STORED);
while (true) {
    $message = $topic->consume(0, 1000);
    if (null !== $message) {
        print_r($message->payload);
    }
}

?>

Step 4: Data processing

After receiving the data, we can process the data and store them in memory. We can use Redis to store data and keep it securely by regularly refreshing the data into the database at the appropriate time.

The sample code is as follows:

<?php

$kafkaConf = new RdKafkaConf();
$kafkaConf->set('metadata.broker.list', 'localhost:9092');//设置kafka连接信息
$kafkaConsumer = new RdKafkaConsumer($kafkaConf);

$topicConf = new RdKafkaTopicConf();
$topicConf->set('auto.offset.reset', 'smallest');

$topic = $kafkaConsumer->newTopic('sample', $topicConf);

$redisClient = new Redis();
$redisClient->connect('127.0.0.1', 6379);

$topic->consumeStart(0, RD_KAFKA_OFFSET_STORED);
while (true) {
    $message = $topic->consume(0, 1000);
    if (null !== $message) {
        $data = json_decode($message->payload);
        $redisClient->hMSet('my_data', [
            $data->key1 => $data->value1,
            $data->key2 => $data->value2,
        ]);
    }
}

?>

Step 5: Data Synchronization

Finally, we need to flush the real-time data stream back to our database. We can use a timer and a PHP process to periodically flush the Redis cache back to the database.

The sample code is as follows:

<?php

$kafkaConf = new RdKafkaConf();
$kafkaConf->set('metadata.broker.list', 'localhost:9092');//设置kafka连接信息
$kafkaConsumer = new RdKafkaConsumer($kafkaConf);

$topicConf = new RdKafkaTopicConf();
$topicConf->set('auto.offset.reset', 'smallest');

$topic = $kafkaConsumer->newTopic('sample', $topicConf);

$redisClient = new Redis();
$redisClient->connect('127.0.0.1', 6379);

$topic->consumeStart(0, RD_KAFKA_OFFSET_STORED);

$count = 0;
while (true) {
    $message = $topic->consume(0, 1000);
    if (null !== $message) {
        $data = json_decode($message->payload);
        $redisClient->hMSet('my_data', [
            $data->key1 => $data->value1,
            $data->key2 => $data->value2,
        ]);
        $count++;
        if ($count == 5) {
            $count = 0;
            $allData = $redisClient->hGetAll('my_data');
            //将数据更新到数据库中
            //...
        }
    }
}

?>

Conclusion

In this article, we introduced how to implement real-time data processing using PHP and Kafka. Real-time data can be easily streamed into a data pipeline using Kafka, and processed and stored using PHP. We also use Redis as cache and in-memory storage to handle real-time data. This approach can easily replace caching and messaging solutions while providing greater performance and scalability.

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