PHP and Apache Kylin integrate to implement OLAP data analysis and statistics

OLAP (Online Analytical Processing) data analysis is an important means of enterprise-level data analysis. As the amount of data increases year by year, the efficiency and complexity of data analysis using traditional relational databases have gradually become difficult to meet demand. Therefore, OLAP database came into being.

In an OLAP database, data is organized according to multiple dimensions (such as time, region, product, etc.) rather than in the form of tables in traditional relational databases. In this way, data analysts can easily perform complex multi-dimensional data query and analysis. PHP and Apache Kylin are two popular open source technologies that can be integrated to implement OLAP data analysis and statistics. Here's how they work.

Apache Kylin is an OLAP engine originally developed by eBay. It started the trend of OLAP on Hadoop and implemented the design of multi-dimensional data model and ultra-fast query engine based on Hadoop, as well as the SQL query language for OLAP. PHP is a commonly used web programming language that is widely used in web application development.

Apache Kylin provides a REST API to interact with data. PHP can use this API to query Apache Kylin. Users can customize multi-dimensional data models and import data into Apache Kylin to build multi-dimensional data cubes. Apache Kylin will build an index based on this cube so that query results can be returned within seconds.

For data warehouse administrators and data analysts, it is more convenient and faster to use PHP to query Apache Kylin. Because PHP has a simple and easy-to-use syntax and a rich function library, it can easily construct and process HTTP requests to manage and query data from Apache Kylin. For example, for PHP developers, the following code can query order data in Apache Kylin, group by time and region, and calculate total sales:

// 设定查询参数
$queryParams = [
    'cubeName' => 'Sales',
    'dimensions' => 'time_dim, region_dim',
    'metrics' => 'sales_total',
    'since' => '2019-01-01',
    'until' => '2019-12-31',
];

// 构造查询URL
$queryUrl = 'http://localhost:7070/kylin/api/query?' . http_build_query($queryParams);

// 执行查询并获取结果
$queryResult = json_decode(file_get_contents($queryUrl), true);

// 输出结果
echo '<pre class="brush:php;toolbar:false">', print_r($queryResult, true), '

';

In the above code, we use PHP’s built-in # The ##http_build_query function is used to construct the query URL, and then the file_get_contents function is used to execute the query and obtain the results. Finally, we output the results to the Web page using the print_r function. In this way, data analysts only need to write simple PHP code to analyze and count data from Apache Kylin, and generate beautiful analysis reports.

In general, the OLAP method integrating PHP and Apache Kylin is an efficient enterprise-level data analysis and statistical method. It allows data analysts and data warehouse administrators to conduct data statistics and analysis more conveniently, and can obtain complex multi-dimensional query results in just a few seconds. I believe that with the continuous development of OLAP data analysis, this method will be more widely used in various fields.

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