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Version: 1.4.0

Linkis SDK Manual

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

Engine pluginDefault supported versionsScript typeType Description
Spark2.4.3pypython script
scalascala script
sqlsql script
Hive2.3.3hqlhql script
Pythonpython2pythonpython script
Shell1shellshell script
JDBC4jdbcsql script name
Flink1.12.2sqlsql script
openLooKeng1.5.0sqlsql script
Pipeline1pipelineFile import and export
Presto0.234psqlsql script
Sqoop1.4.6appconnFile import and export
Elasticsearch7.6.2esjsonjson script
essqlsql script
trino371tsqlsql script

Linkis common label

label keylabel valuedescription
engineTypespark-2.4.3the engine type and version
userCreatoruser + "-AppName"the running user and your AppName
codeTypesqlscript type
jobRunningTimeout10If the job does not finish for 10s, it will automatically initiate Kill. The unit is s
jobQueuingTimeout10If the job queue exceeds 10s and fails to complete, Kill will be automatically initiated. The unit is s
jobRetryTimeout10000The 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
tenanthduser02tenant label

1. Import dependent modules

<dependency>
<groupId>org.apache.linkis</groupId>
<artifactId>linkis-computation-client</artifactId>
<version>${linkis.version}</version>
</dependency>

2. Java test code

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.

3. Scala test code

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

import org.apache.linkis.ujes.client.UJESClient

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)
var 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, AnyRef] = new util.HashMap[String, AnyRef]
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, AnyRef]()
// Support setting engine native parameters,For example: parameters of engines such as spark/hive
val instances: Integer = 2
startupMap.put("spark.executor.instances", instances)
// 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)
}
}

4. Once SDK Usage

The Linkis-cli client supports submitting tasks of the Once type. After the engine process is started, the task will only be run once, and it will be automatically destroyed after the task ends.

OnceEngineConn calls LinkisManager's createEngineConn interface through LinkisManagerClient, and sends the code to the engine created by the user, and then the engine starts to execute

write a test class Use clien conditions

1. Configure the correct and available gateway address:
LinkisJobClient.config().setDefaultServerUrl("http://ip:9001");
2. Write the engine parameters, configuration items, and execution code in the code:
String code = "env {
+ " spark.app.name = \"SeaTunnel\"\n"
+ "spark.executor.instances = 2\n"
+ "spark.executor.cores = 1\n"
+ " spark.executor.memory = \"1g\"\n"
+ "}\n"
+ "\n"
+ "source {\n"
+ "Fake {\n"
+ " result_table_name = \"my_dataset\"\n"
+ " }\n"
+ "\n"
+ "}\n"
+ "\n"
+ "transform {\n"
+ "}\n"
+ "\n"
+ "sink {\n"
+ " Console {}\n"
+ "}";
3. Create an Once mode object: SubmittableSimpleOnceJob:
SubmittableSimpleOnceJob = LinkisJobClient.once()
.simple()
.builder()
.setCreateService("seatunnel-Test")
.setMaxSubmitTime(300000) timeout
.addLabel(LabelKeyUtils.ENGINE_TYPE_LABEL_KEY(), "seatunnel-2.1.2") engine label
.addLabel(LabelKeyUtils.USER_CREATOR_LABEL_KEY(), "hadoop-seatunnel") user label
.addLabel(LabelKeyUtils.ENGINE_CONN_MODE_LABEL_KEY(), "once") engine mode label
.addStartupParam(Configuration.IS_TEST_MODE().key(), true) Whether to enable the test mode
.addExecuteUser("hadoop") execute user
.addJobContent("runType", "spark") execution engine
.addJobContent("code", code) execute code
.addJobContent("master", "local[4]")
.addJobContent("deploy-mode", "client")
.addSource("jobName", "OnceJobTest") name
.build();

Test class sample code:

package org.apache.linkis.ujes.client

import org.apache.linkis.common.utils.Utils
import java.util.concurrent.TimeUnit
import java.util
import org.apache.linkis.computation.client.LinkisJobBuilder
import org.apache.linkis.computation.client.once.simple.{SimpleOnceJob, SimpleOnceJobBuilder, SubmittableSimpleOnceJob}
import org.apache.linkis.computation.client.operator.impl.{EngineConnLogOperator, EngineConnMetricsOperator, EngineConnProgressOperator}
import org.apache.linkis.computation.client.utils.LabelKeyUtils
import scala.collection.JavaConverters._

object SqoopOnceJobTest extends App {
LinkisJobBuilder.setDefaultServerUrl("http://gateway address:9001")
val logPath = "C:\\Users\\resources\\log4j.properties"
System.setProperty("log4j.configurationFile", logPath)
val startUpMap = new util. HashMap[String, AnyRef]
startUpMap.put("wds.linkis.engineconn.java.driver.memory", "1g")
val builder = SimpleOnceJob. builder(). setCreateService("Linkis-Client")
.addLabel(LabelKeyUtils.ENGINE_TYPE_LABEL_KEY, "sqoop-1.4.6")
.addLabel(LabelKeyUtils.USER_CREATOR_LABEL_KEY, "hadoop-Client")
.addLabel(LabelKeyUtils.ENGINE_CONN_MODE_LABEL_KEY, "once")
.setStartupParams(startUpMap)
.setMaxSubmitTime(30000)
.addExecuteUser("hadoop")
val onceJob = importJob(builder)
val time = System. currentTimeMillis()
onceJob. submit()
println(onceJob. getId)
val logOperator = onceJob.getOperator(EngineConnLogOperator.OPERATOR_NAME).asInstanceOf[EngineConnLogOperator]
println(onceJob. getECMServiceInstance)
logOperator. setFromLine(0)
logOperator.setECMServiceInstance(onceJob.getECMServiceInstance)
logOperator.setEngineConnType("sqoop")
logOperator.setIgnoreKeywords("[main],[SpringContextShutdownHook]")
var progressOperator = onceJob.getOperator(EngineConnProgressOperator.OPERATOR_NAME).asInstanceOf[EngineConnProgressOperator]
var metricOperator = onceJob.getOperator(EngineConnMetricsOperator.OPERATOR_NAME).asInstanceOf[EngineConnMetricsOperator]
var end = false
var rowBefore = 1
while (!end || rowBefore > 0) {
if (onceJob. isCompleted) {
end = true
metricOperator = null
}
logOperator. setPageSize(100)
Utils. tryQuietly {
val logs = logOperator.apply()
logs. logs. asScala. foreach(log => {
println(log)
})
rowBefore = logs. logs. size
}
Thread. sleep(3000)
Option(metricOperator).foreach(operator => {
if (!onceJob.isCompleted) {
println(s"Metric monitoring: ${operator.apply()}")
println(s"Progress: ${progressOperator.apply()}")
}
})
}
onceJob. isCompleted
onceJob. waitForCompleted()
println(onceJob. getStatus)
println(TimeUnit. SECONDS. convert(System. currentTimeMillis() - time, TimeUnit. MILLISECONDS) + "s")
System. exit(0)

def importJob(jobBuilder: SimpleOnceJobBuilder): SubmittableSimpleOnceJob = {
jobBuilder
.addJobContent("sqoop.env.mapreduce.job.queuename", "queue_1003_01")
.addJobContent("sqoop. mode", "import")
.addJobContent("sqoop.args.connect", "jdbc:mysql://database address/library name")
.addJobContent("sqoop.args.username", "database account")
.addJobContent("sqoop.args.password", "database password")
.addJobContent("sqoop.args.query", "select * from linkis_ps_udf_manager where 1=1 and $CONDITIONS")
#The table must exist $CONDITIONS is indispensable
.addJobContent("sqoop.args.hcatalog.database", "janicegong_ind")
.addJobContent("sqoop.args.hcatalog.table", "linkis_ps_udf_manager_sync2")
.addJobContent("sqoop.args.hcatalog.partition.keys", "ds")
.addJobContent("sqoop.args.hcatalog.partition.values", "20220708")
.addJobContent("sqoop.args.num.mappers", "1")
.build()
}
def exportJob(jobBuilder: SimpleOnceJobBuilder): SubmittableSimpleOnceJob = {
jobBuilder
.addJobContent("sqoop.env.mapreduce.job.queuename", "queue_1003_01")
.addJobContent("sqoop. mode", "import")
.addJobContent("sqoop.args.connect", "jdbc:mysql://database address/library name")
.addJobContent("sqoop.args.username", "database account")
.addJobContent("sqoop.args.password", "database password")
.addJobContent("sqoop.args.query", "select * from linkis_ps_udf_manager where 1=1 and $CONDITIONS")
#The table must exist $CONDITIONS is indispensable
.addJobContent("sqoop.args.hcatalog.database", "janicegong_ind")
.addJobContent("sqoop.args.hcatalog.table", "linkis_ps_udf_manager_sync2")
.addJobContent("sqoop.args.hcatalog.partition.keys", "ds")
.addJobContent("sqoop.args.hcatalog.partition.values", "20220708")
.addJobContent("sqoop.args.num.mappers", "1")
.build
}
}