Linkis provides a convenient interface for JAVA and SCALA calls. You only need to import the linkis-computation-client module to use it. After 1.0, it supports the method of submitting with Label. The following will introduce the way to use the SDK.
Engine version and script type supported by Linkis
Linkis common label
| label key | label value | description |
|---|---|---|
| engineType | spark-2.4.3 | the engine type and version |
| userCreator | user + “-AppName” | the running user and your AppName |
| codeType | sql | script type |
| jobRunningTimeout | 10 | If the job does not finish for 10s, it will automatically initiate Kill. The unit is s |
| jobQueuingTimeout | 10 | If the job queue exceeds 10s and fails to complete, Kill will be automatically initiated. The unit is s |
| jobRetryTimeout | 10000 | The waiting time for a job to fail due to resources or other reasons is ms. If a job fails due to insufficient queue resources, the retry is initiated 10 times by default |
| tenant | hduser02 | tenant label |
<dependency>
<groupId>org.apache.linkis</groupId>
<artifactId>linkis-computation-client</artifactId>
<version>${linkis.version}</version>
</dependency>
Create a Java test class LinkisClientTest, the specific interface meaning can be found in the notes:
package org.apache.linkis.client.test; import org.apache.linkis.common.utils.Utils; import org.apache.linkis.httpclient.dws.authentication.StaticAuthenticationStrategy; import org.apache.linkis.httpclient.dws.config.DWSClientConfig; import org.apache.linkis.httpclient.dws.config.DWSClientConfigBuilder; import org.apache.linkis.manager.label.constant.LabelKeyConstant; import org.apache.linkis.protocol.constants.TaskConstant; import org.apache.linkis.ujes.client.UJESClient; import org.apache.linkis.ujes.client.UJESClientImpl; import org.apache.linkis.ujes.client.request.JobSubmitAction; import org.apache.linkis.ujes.client.request.JobExecuteAction; import org.apache.linkis.ujes.client.request.ResultSetAction; import org.apache.linkis.ujes.client.response.*; import org.apache.commons.io.IOUtils; import java.util.HashMap; import java.util.Map; import java.util.concurrent.TimeUnit; public class LinkisClientTest { // 1. build config: linkis gateway url private static DWSClientConfig clientConfig = ((DWSClientConfigBuilder) (DWSClientConfigBuilder.newBuilder() .addServerUrl("http://127.0.0.1:9001/") //set linkis-mg-gateway url: http://{ip}:{port} .connectionTimeout(30000) //connectionTimeOut .discoveryEnabled(false) //disable discovery .discoveryFrequency(1, TimeUnit.MINUTES) // discovery frequency .loadbalancerEnabled(true) // enable loadbalance .maxConnectionSize(5) // set max Connection .retryEnabled(false) // set retry .readTimeout(30000) //set read timeout .setAuthenticationStrategy(new StaticAuthenticationStrategy()) //AuthenticationStrategy Linkis authen suppory static and Token .setAuthTokenKey("hadoop") // set submit user .setAuthTokenValue("123456"))) // set passwd or token (setAuthTokenValue("test")) .setDWSVersion("v1") //linkis rest version v1 .build(); // 2. new Client(Linkis Client) by clientConfig private static UJESClient client = new UJESClientImpl(clientConfig); public static void main(String[] args) { // The user needs to be consistent with the value of AuthTokenKey String user = "hadoop"; String executeCode = "df=spark.sql(\"show tables\")\n" + "show(df)"; // code support:sql/hql/py/scala try { System.out.println("user : " + user + ", code : [" + executeCode + "]"); // 3. build job and execute JobExecuteResult jobExecuteResult = toSubmit(user, executeCode); System.out.println("execId: " + jobExecuteResult.getExecID() + ", taskId: " + jobExecuteResult.taskID()); // 4. get job info JobInfoResult jobInfoResult = client.getJobInfo(jobExecuteResult); int sleepTimeMills = 1000; int logFromLen = 0; int logSize = 100; while (!jobInfoResult.isCompleted()) { // 5. get progress and log JobProgressResult progress = client.progress(jobExecuteResult); System.out.println("progress: " + progress.getProgress()); JobLogResult logRes = client.log(jobExecuteResult, logFromLen, logSize); logFromLen = logRes.fromLine(); // 0: info 1: warn 2: error 3: all System.out.println(logRes.log().get(3)); Utils.sleepQuietly(sleepTimeMills); jobInfoResult = client.getJobInfo(jobExecuteResult); } JobInfoResult jobInfo = client.getJobInfo(jobExecuteResult); // 6. Get the result set list (if the user submits multiple SQLs at a time, // multiple result sets will be generated) String resultSet = jobInfo.getResultSetList(client)[0]; // 7. get resultContent ResultSetResult resultSetResult = client.resultSet(ResultSetAction.builder().setPath(resultSet).setUser(jobExecuteResult.getUser()).build()); System.out.println("metadata: " + resultSetResult.getMetadata()); // column name type System.out.println("res: " + resultSetResult.getFileContent()); //row data } catch (Exception e) { e.printStackTrace();// please use log IOUtils.closeQuietly(client); } IOUtils.closeQuietly(client); } private static JobExecuteResult toSubmit(String user, String code) { // 1. build params // set label map :EngineTypeLabel/UserCreatorLabel/EngineRunTypeLabel/Tenant Map<String, Object> labels = new HashMap<String, Object>(); labels.put(LabelKeyConstant.ENGINE_TYPE_KEY, "spark-2.4.3"); // required engineType Label labels.put(LabelKeyConstant.USER_CREATOR_TYPE_KEY, user + "-APPName");// required execute user and creator eg:hadoop-IDE labels.put(LabelKeyConstant.CODE_TYPE_KEY, "py"); // required codeType // set start up map :engineConn start params Map<String, Object> startupMap = new HashMap<String, Object>(16); // Support setting engine native parameters,For example: parameters of engines such as spark/hive startupMap.put("spark.executor.instances", 2); // setting linkis params startupMap.put("wds.linkis.rm.yarnqueue", "dws"); // 2. build jobSubmitAction JobSubmitAction jobSubmitAction = JobSubmitAction.builder() .addExecuteCode(code) .setStartupParams(startupMap) .setUser(user) //submit user .addExecuteUser(user) // execute user .setLabels(labels) . .build(); // 3. to execute return client.submit(jobSubmitAction); } }
Run the above code to complete task submission/execution/log/result set acquisition, etc.
package org.apache.linkis.client.test import org.apache.commons.io.IOUtils import org.apache.commons.lang3.StringUtils import org.apache.linkis.common.utils.Utils import org.apache.linkis.httpclient.dws.authentication.StaticAuthenticationStrategy import org.apache.linkis.httpclient.dws.config.DWSClientConfigBuilder import org.apache.linkis.manager.label.constant.LabelKeyConstant import org.apache.linkis.ujes.client.request._ import org.apache.linkis.ujes.client.response._ import java.util import java.util.concurrent.TimeUnit object LinkisClientTest { // 1. build config: linkis gateway url val clientConfig = DWSClientConfigBuilder.newBuilder() .addServerUrl("http://127.0.0.1:9001/") //set linkis-mg-gateway url: http://{ip}:{port} .connectionTimeout(30000) //connectionTimeOut .discoveryEnabled(false) //disable discovery .discoveryFrequency(1, TimeUnit.MINUTES) // discovery frequency .loadbalancerEnabled(true) // enable loadbalance .maxConnectionSize(5) // set max Connection .retryEnabled(false) // set retry .readTimeout(30000) //set read timeout .setAuthenticationStrategy(new StaticAuthenticationStrategy()) //AuthenticationStrategy Linkis authen suppory static and Token .setAuthTokenKey("hadoop") // set submit user .setAuthTokenValue("hadoop") // set passwd or token (setAuthTokenValue("BML-AUTH")) .setDWSVersion("v1") //link rest version v1 .build(); // 2. new Client(Linkis Client) by clientConfig val client = UJESClient(clientConfig) def main(args: Array[String]): Unit = { val user = "hadoop" // execute user user needs to be consistent with the value of AuthTokenKey val executeCode = "df=spark.sql(\"show tables\")\n" + "show(df)"; // code support:sql/hql/py/scala try { // 3. build job and execute println("user : " + user + ", code : [" + executeCode + "]") // It is recommended to use submit, which supports the transfer of task labels val jobExecuteResult = toSubmit(user, executeCode) println("execId: " + jobExecuteResult.getExecID + ", taskId: " + jobExecuteResult.taskID) // 4. get job info var jobInfoResult = client.getJobInfo(jobExecuteResult) where logFromLen = 0 val logSize = 100 val sleepTimeMills: Int = 1000 while (!jobInfoResult.isCompleted) { // 5. get progress and log val progress = client.progress(jobExecuteResult) println("progress: " + progress.getProgress) val logObj = client.log(jobExecuteResult, logFromLen, logSize) logFromLen = logObj.fromLine val logArray = logObj.getLog // 0: info 1: warn 2: error 3: all if (logArray != null && logArray.size >= 4 && StringUtils.isNotEmpty(logArray.get(3))) { println(s"log: ${logArray.get(3)}") } Utils.sleepQuietly(sleepTimeMills) jobInfoResult = client.getJobInfo(jobExecuteResult) } if (!jobInfoResult.isSucceed) { println("Failed to execute job: " + jobInfoResult.getMessage) throw new Exception(jobInfoResult.getMessage) } // 6. Get the result set list (if the user submits multiple SQLs at a time, // multiple result sets will be generated) val jobInfo = client.getJobInfo(jobExecuteResult) val resultSetList = jobInfoResult.getResultSetList(client) println("All result set list:") resultSetList.foreach(println) val oneResultSet = jobInfo.getResultSetList(client).head // 7. get resultContent val resultSetResult: ResultSetResult = client.resultSet(ResultSetAction.builder.setPath(oneResultSet).setUser(jobExecuteResult.getUser).build) println("metadata: " + resultSetResult.getMetadata) // column name type println("res: " + resultSetResult.getFileContent) //row data } catch { case e: Exception => { e.printStackTrace() //please use log } } IOUtils.closeQuietly(client) } def toSubmit(user: String, code: String): JobExecuteResult = { // 1. build params // set label map :EngineTypeLabel/UserCreatorLabel/EngineRunTypeLabel/Tenant val labels: util.Map[String, Any] = new util.HashMap[String, Any] labels.put(LabelKeyConstant.ENGINE_TYPE_KEY, "spark-2.4.3"); // required engineType Label labels.put(LabelKeyConstant.USER_CREATOR_TYPE_KEY, user + "-APPName"); // The requested user and application name, both parameters must be missing, where APPName cannot contain "-", it is recommended to replace it with "_" labels.put(LabelKeyConstant.CODE_TYPE_KEY, "py"); // specify the script type val startupMap = new java.util.HashMap[String, Any]() // Support setting engine native parameters,For example: parameters of engines such as spark/hive startupMap.put("spark.executor.instances", 2); // setting linkis params startupMap.put("wds.linkis.rm.yarnqueue", "default"); // 2. build jobSubmitAction val jobSubmitAction = JobSubmitAction.builder .addExecuteCode(code) .setStartupParams(startupMap) .setUser(user) //submit user .addExecuteUser(user) //execute user .setLabels(labels) . .build // 3. to execute client.submit(jobSubmitAction) } }