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Help Center/ Data Lake Insight/ Developer Guide/ Flink Jobs/ Flink Job Agencies/ Flink Jar Jobs Using DEW to Acquire Access Credentials for Reading and Writing Data from and to OBS

Flink Jar Jobs Using DEW to Acquire Access Credentials for Reading and Writing Data from and to OBS

Updated on 2024-09-20 GMT+08:00

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Scenario

To write the output data of a Flink Jar job to OBS, AK/SK is required for accessing OBS. To ensure the security of AK/SK data, you can use Data Encryption Workshop (DEW) and Cloud Secret Management Service (CSMS) for unified management of AK/SK, effectively avoiding sensitive information leakage and business risks caused by hard-coded or plaintext configuration of programs.

This section walks you through on how a Flink Jar job acquires an AK/SK to read and write data from and to OBS.

Prerequisites

A shared secret has been created on the DEW console and the secret value has been stored. For details, see Creating a Shared Secret.
An agency has been created and authorized for DLI to access DEW. The agency must have been granted the following permissions:
- Permission of the ShowSecretVersion interface for querying secret versions and secret values in DEW: csms:secretVersion:get.
- Permission of the ListSecretVersions interface for listing secret versions in DEW: csms:secretVersion:list.
- Permission to decrypt DEW secrets: kms:dek:decrypt
For details about agency permission examples, see Customizing DLI Agency Permissions and Agency Permission Policies in Common Scenarios.
DEW can be used to manage access credentials only in Flink 1.15. When creating a Flink job, select version 1.15 and configure the information of the agency that allows DLI to access DEW for the job. For details about how to create a custom agency and configure it, see Customizing DLI Agency Permissions.
To use this function, you need to configure AK/SK for all OBS buckets.

Syntax

On the Flink Jar job editing page, set Runtime Configuration as needed. The configuration information is as follows:

Different OBS buckets use different AK/SK authentication information. You can use the following configuration method to specify the AK/SK information based on the bucket. For details about the parameters, see Table 1.

flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.access.key=USER_AK_CSMS_KEY
flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.secret.key=USER_SK_CSMS_KEY
flink.hadoop.fs.obs.security.provider=com.dli.provider.UserObsBasicCredentialProvider
flink.hadoop.fs.dew.csms.secretName=CredentialName
flink.hadoop.fs.dew.endpoint=ENDPOINT
flink.hadoop.fs.dew.csms.version=VERSION_ID
flink.hadoop.fs.dew.csms.cache.time.second=CACHE_TIME
flink.dli.job.agency.name=USER_AGENCY_NAME

Parameter Description

**Table 1** Parameters
Parameter	Mandatory	Default Value	Data Type	Description
flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.access.key	Yes	None	String	USER_BUCKET_NAME needs to be replaced with the user's OBS bucket name. The value of this parameter is the key defined by the user in the CSMS shared secret. The value corresponding to the key is the user's access key ID (AK). The user must have the permission to access the bucket on OBS.
flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.secret.key	Yes	None	String	USER_BUCKET_NAME needs to be replaced with the user's OBS bucket name. The value of this parameter is the key defined by the user in the CSMS shared secret. The value corresponding to the key is the user's secret access key (SK). The user must have the permission to access the bucket on OBS.
flink.hadoop.fs.obs.security.provider	Yes	None	String	OBS AK/SK authentication mechanism, which uses DEW-CSMS' secret management to obtain the AK and SK for accessing OBS. The default value is com.dli.provider.UserObsBasicCredentialProvider.
flink.hadoop.fs.dew.endpoint	Yes	None	String	Endpoint of the DEW service to be used. See Regions and Endpoints. Configuration example: flink.hadoop.fs.dew.endpoint=kms.cn-xxxx.myhuaweicloud.com
flink.hadoop.fs.dew.projectId	No	Yes	String	ID of the project DEW belongs to. The default value is the ID of the project where the Flink job is. See Obtaining a Project ID.
flink.hadoop.fs.dew.csms.secretName	Yes	None	String	Name of the shared secret in DEW's secret management. Configuration example: flink.hadoop.fs.dew.csms.secretName=secretInfo
flink.hadoop.fs.dew.csms.version	No	Latest version	String	Version number (certificate version identifier) of the shared secret in DEW's secret management. If not specified, the latest version of the shared secret is obtained by default. Configuration example: flink.hadoop.fs.dew.csms.version=v1
flink.hadoop.fs.dew.csms.cache.time.second	No	3600	Long	Cache duration after the CSMS shared secret is obtained during Flink job access. The unit is second. The default value is 3600 seconds.
flink.dli.job.agency.name	Yes	-	String	Custom agency name.

Sample Code

This section describes how to write processed DataGen data to OBS. You need to modify the parameters in the sample Java code based on site requirements.

Create an agency for DLI to access DEW and complete authorization. For details, see Customizing DLI Agency Permissions.
Create a shared secret in DEW. For details, see Creating a Shared Secret.
1. Log in to the DEW management console.
2. In the navigation pane on the left, choose Cloud Secret Management Service > Secrets.
3. On the displayed page, click Create Secret. Set basic secret information.

Set job parameters on the DLI Flink Jar job editing page.

Class Name
```
com.dli.demo.dew.DataGen2FileSystemSink
```

Class Arguments

--checkpoint.path obs://test/flink/jobs/checkpoint/120891/ 
--output.path obs://dli/flink.db/79914/DataGen2FileSystemSink

Runtime Configuration

flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.access.key=USER_AK_CSMS_KEY
flink.hadoop.fs.obs.bucket.USER_BUCKET_NAME.dew.secret.key=USER_SK_CSMS_KEY
flink.hadoop.fs.obs.security.provider=com.dli.provider.UserObsBasicCredentialProvider
flink.hadoop.fs.dew.csms.secretName=obsAksK
flink.hadoop.fs.dew.endpoint=kmsendpoint
flink.hadoop.fs.dew.csms.version=v6
flink.hadoop.fs.dew.csms.cache.time.second=3600
flink.dli.job.agency.name=***

Flink Jar job example.

Environment preparation

Development tools such as IntelliJ IDEA and other development tools, JDK, and Maven have been installed and configured.

Dependency package in POM file configurations

 <properties>
        <flink.version>1.15.0</flink.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>

        <!-- fastjson -->
        <dependency>
            <artifactId>fastjson</artifactId>
            <version>2.0.15</version>
        </dependency>
    </dependencies>

Sample code

package com.huawei.dli.demo.dew;

import org.apache.flink.api.common.serialization.SimpleStringEncoder;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.contrib.streaming.state.EmbeddedRocksDBStateBackend;
import org.apache.flink.core.fs.Path;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink;
import org.apache.flink.streaming.api.functions.sink.filesystem.rollingpolicies.OnCheckpointRollingPolicy;
import org.apache.flink.streaming.api.functions.source.ParallelSourceFunction;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.time.LocalDateTime;
import java.time.ZoneOffset;
import java.time.format.DateTimeFormatter;
import java.util.Random;

public class DataGen2FileSystemSink {
    private static final Logger LOG = LoggerFactory.getLogger(DataGen2FileSystemSink.class);

    public static void main(String[] args) {
        ParameterTool params = ParameterTool.fromArgs(args);
        LOG.info("Params: " + params.toString());
        try {
            StreamExecutionEnvironment streamEnv = StreamExecutionEnvironment.getExecutionEnvironment();

            // set checkpoint
            String checkpointPath = params.get("checkpoint.path", "obs://bucket/checkpoint/jobId_jobName/");
            LocalDateTime localDateTime = LocalDateTime.ofEpochSecond(System.currentTimeMillis() / 1000,
                0, ZoneOffset.ofHours(8));
            String dt = localDateTime.format(DateTimeFormatter.ofPattern("yyyyMMdd_HH:mm:ss"));
            checkpointPath = checkpointPath + dt;

            streamEnv.setStateBackend(new EmbeddedRocksDBStateBackend());
            streamEnv.getCheckpointConfig().setCheckpointStorage(checkpointPath);
            streamEnv.getCheckpointConfig().setExternalizedCheckpointCleanup(
                CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
            streamEnv.enableCheckpointing(30 * 1000);

            DataStream<String> stream = streamEnv.addSource(new DataGen())
                .setParallelism(1)
                .disableChaining();

            String outputPath = params.get("output.path", "obs://bucket/outputPath/jobId_jobName");

            // Sink OBS
            final StreamingFileSink<String> sinkForRow = StreamingFileSink
                .forRowFormat(new Path(outputPath), new SimpleStringEncoder<String>("UTF-8"))
                .withRollingPolicy(OnCheckpointRollingPolicy.build())
                .build();

            stream.addSink(sinkForRow);

            streamEnv.execute("sinkForRow");
        } catch (Exception e) {
            LOG.error(e.getMessage(), e);
        }
    }
}

class DataGen implements ParallelSourceFunction<String> {

    private boolean isRunning = true;

    private Random random = new Random();

    @Override
    public void run(SourceContext<String> ctx) throws Exception {
        while (isRunning) {
            JSONObject jsonObject = new JSONObject();
            jsonObject.put("id", random.nextLong());
            jsonObject.put("name", "Molly" + random.nextInt());
            jsonObject.put("address", "hangzhou" + random.nextInt());
            jsonObject.put("birthday", System.currentTimeMillis());
            jsonObject.put("city", "hangzhou" + random.nextInt());
            jsonObject.put("number", random.nextInt());
            ctx.collect(jsonObject.toJSONString());
            Thread.sleep(1000);
        }
    }

    @Override
    public void cancel() {
        isRunning = false;
    }
}

Parent topic: Flink Job Agencies

Previous topic: Flink OpenSource SQL Jobs Using DEW to Manage Access Credentials

Next topic: Obtaining Temporary Credentials from a Flink Job's Agency for Accessing Other Cloud Services

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