How to use Java to develop a real-time analysis and query application based on Apache Druid

How to use Java to develop a real-time analysis and query application based on Apache Druid

Introduction:
Apache Druid is an open source real-time data processing and query engine. It features high performance, scalability and reliability and is suitable for building real-time analysis and query applications. This article will introduce how to use Java language to develop a real-time analysis and query application based on Apache Druid, and provide specific code examples.

1. Set up the Apache Druid environment
First, we need to set up the Apache Druid environment. The specific steps are as follows:

1. Download and unzip the Apache Druid installation package.
2. Configure Druid's environment variables, including JAVA_HOME and DRUID_HOME.
3. Start the Zookeeper service.
4. Start the Druid service, including Broker, Coordinator, Overlord and Historical nodes.

2. Create a Druid data source
Next, we need to create a Druid data source and import the data into Druid. The specific steps are as follows:

1. Create a data source containing necessary fields, such as timestamp, dimension and measure fields.
2. Use Java code to connect to Druid's Coordinator node and create a data source.
3. Use Java code to import data into Druid's data source. Specific code examples are as follows:

DruidDataSource dataSource = new DruidDataSource();
dataSource.setUrl("jdbc:mysql://localhost:3306/mydb");
dataSource.setUsername("root");
dataSource.setPassword("password");

String jsonPath = "path/to/data.json";
String dataSourceName = "myDataSource";

File jsonFile = new File(jsonPath);
InputStream inputStream = new FileInputStream(jsonFile);
InputStreamReader reader = new InputStreamReader(inputStream);

String data = IOUtils.toString(reader);
String jsonPayload = String.format(data, dataSourceName);

HttpURLConnection connection = (HttpURLConnection) new URL("http://localhost:8081/druid/coordinator/v1/metadata/datasources").openConnection();
connection.setRequestMethod("POST");
connection.setDoOutput(true);

OutputStream outputStream = connection.getOutputStream();
outputStream.write(jsonPayload.getBytes());
outputStream.close();

int responseCode = connection.getResponseCode();
if (responseCode == 200) {
    System.out.println("Data source created successfully.");
}

3. Write Druid query code
Once the data source is successfully created and the data import is completed, we can write the Druid query code. The specific steps are as follows:

1. Use Java code to connect to Druid’s Broker node.
2. Construct a Druid query request and send it to the Druid cluster. The specific code examples are as follows:

DruidQueryRequest queryRequest = new DruidQueryRequest();
queryRequest.setDataSource("myDataSource");
queryRequest.setGranularity("hour");
queryRequest.setIntervals("2022-01-01T00:00:00Z/2022-01-02T00:00:00Z");

DruidAggregation aggregation = new DruidAggregation();
aggregation.setType("longSum");
aggregation.setName("totalClicks");
aggregation.setFieldName("clicks");

queryRequest.setAggregations(Collections.singletonList(aggregation));

URL url = new URL("http://localhost:8082/druid/v2");
HttpURLConnection connection = (HttpURLConnection) url.openConnection();
connection.setRequestMethod("POST");
connection.setDoOutput(true);

Gson gson = new Gson();
String jsonPayload = gson.toJson(queryRequest);

OutputStream outputStream = connection.getOutputStream();
outputStream.write(jsonPayload.getBytes());
outputStream.close();

int responseCode = connection.getResponseCode();
if (responseCode == 200) {
    InputStream inputStream = connection.getInputStream();
    InputStreamReader reader = new InputStreamReader(inputStream);
    String result = IOUtils.toString(reader);
    System.out.println(result);
}

4. Display the query results
Finally, we need to display or process the query results. Specific code examples are as follows:

JsonParser parser = new JsonParser();
JsonObject jsonObject = parser.parse(result).getAsJsonObject();
JsonArray events = jsonObject.getAsJsonArray("events");

for (JsonElement event : events) {
    JsonObject eventObject = event.getAsJsonObject();
    String timestamp = eventObject.get("__time").getAsString();
    long clicks = eventObject.get("totalClicks").getAsLong();

    System.out.println("Timestamp: " + timestamp);
    System.out.println("Total Clicks: " + clicks);
}

Conclusion:
This article introduces how to use Java language to develop a real-time analysis and query application based on Apache Druid, including building a Druid environment, creating a Druid data source, and writing Druid query code and display query results. Through these steps, we can easily build a powerful real-time analysis and query application to help us quickly perform data analysis and decision-making.

Reference materials:

1. Apache Druid official documentation: https://druid.apache.org/
2. Druid sample code on GitHub: https:// github.com/apache/druid/tree/master/examples/quickstart

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