Sqoop 引擎
本文主要介绍Sqoop(>=1.1.2 版本支持)引擎的配置、部署和使用。
Sqoop引擎主要依赖Hadoop基础环境,如果该节点需要部署Sqoop引擎,需要部署Hadoop客户端环境。
强烈建议您在执行Sqoop任务之前,先在该节点使用原生的Sqoop执行测试任务,以检测该节点环境是否正常。
#验证sqoop环境是否可用 参考示例:将hdfs的/user/hive/warehouse/hadoop/test_linkis_sqoop文件数据导入到mysql表 test_sqoop中
sqoop export \
--connect jdbc:mysql://10.10.10.10/test \
--username test \
--password test123\
--table test_sqoop \
--columns user_id,user_code,user_name,email,status \
--export-dir /user/hive/warehouse/hadoop/test_linkis_sqoop \
--update-mode allowinsert \
--verbose ;
环境变量名 | 环境变量内容 | 备注 |
---|---|---|
JAVA_HOME | JDK安装路径 | 必须 |
HADOOP_HOME | Hadoop安装路径 | 必须 |
HADOOP_CONF_DIR | Hadoop配置路径 | 必须 |
SQOOP_HOME | Sqoop安装路径 | 必须 |
SQOOP_CONF_DIR | Sqoop配置路径 | 非必须 |
HCAT_HOME | HCAT配置路径 | 非必须 |
HBASE_HOME | HBASE配置路径 | 非必须 |
表1-1 环境配置清单
Linkis系统参数 | 参数 | 备注 |
---|---|---|
wds.linkis.hadoop.site.xml | 设置sqoop加载hadoop参数文件位置 | 一般不需要单独配置,默认值”core-site.xml;hdfs-site.xml;yarn-site.xml;mapred-site.xml” |
sqoop.fetch.status.interval | 设置获取sqoop执行状态的间隔时间 | 一般不需要单独配置,默认值为5s |
Linkis 1.1.2及以上支持的主流Sqoop版本1.4.6与1.4.7,更高版本可能需要修改部分代码重新编译。
注意: 编译sqoop引擎之前需要进行linkis项目全量编译
单独编译sqoop的方式
${linkis_code_dir}/linkis-engineconn-plugins/sqoop/
mvn clean install
安装方式是将编译出来的引擎包,位置在
${linkis_code_dir}/linkis-enginepconn-plugins/engineconn-plugins/sqoop/target/sqoop-engineconn.zip
然后上传部署到linkis服务器
${LINKIS_HOME}/lib/linkis-engineplugins
并重启linkis-engineplugin
cd ${LINKIS_HOME}/sbin
sh linkis-daemon.sh restart cg-engineplugin
engineplugin更详细的介绍可以参看下面的文章。
https://linkis.apache.org/zh-CN/docs/latest/deployment/install-engineconn
hdfs文件导出到mysql
sh linkis-cli-sqoop export \
-D mapreduce.job.queuename=ide \
--connect jdbc:mysql://10.10.10.10:9600/testdb \
--username password@123 \
--password password@123 \
--table test_sqoop_01_copy \
--columns user_id,user_code,user_name,email,status \
--export-dir /user/hive/warehouse/hadoop/test_linkis_sqoop_2 \
--update-mode allowinsert --verbose ;
mysql数据导入到hive库
mysql导入到hive 库linkis_test_ind.test_import_sqoop_1,表test_import_sqoop_1不存在 需要添加参数 --create-hive-table
sh linkis-cli-sqoop import -D mapreduce.job.queuename=dws \
--connect jdbc:mysql://10.10.10.10:3306/casion_test \
--username hadoop \
--password password@123 \
--table test_sqoop_01 \
--columns user_id,user_code,user_name,email,status \
--fields-terminated-by ',' \
--hive-import --create-hive-table \
--hive-database casionxia_ind \
--hive-table test_import_sqoop_1 \
--hive-drop-import-delims \
--delete-target-dir \
--input-null-non-string '\\N' \
--input-null-string '\\N' \
--verbose ;
mysql导入到hive 库linkis_test_ind.test_import_sqoop_1,表test_import_sqoop_1存在 移除参数--create-hive-table \
sh linkis-cli-sqoop import -D mapreduce.job.queuename=dws \
--connect jdbc:mysql://10.10.10.10:9600/testdb \
--username testdb \
--password password@123 \
--table test_sqoop_01 \
--columns user_id,user_code,user_name,email,status \
--fields-terminated-by ',' \
--hive-import \
--hive-database linkis_test_ind \
--hive-table test_import_sqoop_1 \
--hive-overwrite \
--hive-drop-import-delims \
--delete-target-dir \
--input-null-non-string '\\N' \
--input-null-string '\\N' \
--verbose ;
OnceEngineConn的使用方式是通过LinkisManagerClient调用LinkisManager的createEngineConn的接口,并将代码发给创建的Sqoop引擎,然后Sqoop引擎就开始执行,此方式可以被其他系统进行调用,比如Exchangis。Client的使用方式也很简单,首先新建一个maven项目,或者在您的项目中引入以下的依赖
<dependency>
<groupId>org.apache.linkis</groupId>
<artifactId>linkis-computation-client</artifactId>
<version>${linkis.version}</version>
</dependency>
测试用例:
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://127.0.0.1:9001")
val logPath = "C:\\Users\\resources\\log4j.properties"
System.setProperty("log4j.configurationFile", logPath)
val startUpMap = new util.HashMap[String, Any]
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, "Client")
.addLabel(LabelKeyUtils.ENGINE_CONN_MODE_LABEL_KEY, "once")
.setStartupParams(startUpMap)
.setMaxSubmitTime(30000)
.addExecuteUser("freeuser")
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监控: ${operator.apply()}")
println(s"进度: ${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_10")
.addJobContent("sqoop.mode", "import")
.addJobContent("sqoop.args.connect", "jdbc:mysql://127.0.0.1:3306/exchangis")
.addJobContent("sqoop.args.username", "free")
.addJobContent("sqoop.args.password", "testpwd")
.addJobContent("sqoop.args.query", "select id as order_number, sno as time from" +
" exchangis where sno =1 and $CONDITIONS")
.addJobContent("sqoop.args.hcatalog.database", "freedb")
.addJobContent("sqoop.args.hcatalog.table", "zy_test")
.addJobContent("sqoop.args.hcatalog.partition.keys", "month")
.addJobContent("sqoop.args.hcatalog.partition.values", "3")
.addJobContent("sqoop.args.num.mappers", "1")
.build()
}
def exportJob(jobBuilder: SimpleOnceJobBuilder): SubmittableSimpleOnceJob = {
jobBuilder
.addJobContent("sqoop.env.mapreduce.job.queuename", "queue1")
.addJobContent("sqoop.mode", "import")
.addJobContent("sqoop.args.connect", "jdbc:mysql://127.0.0.1:3306/exchangis")
.addJobContent("sqoop.args.query", "select id as order, sno as great_time from" +
" exchangis_table where sno =1 and $CONDITIONS")
.addJobContent("sqoop.args.hcatalog.database", "hadoop")
.addJobContent("sqoop.args.hcatalog.table", "partition_33")
.addJobContent("sqoop.args.hcatalog.partition.keys", "month")
.addJobContent("sqoop.args.hcatalog.partition.values", "4")
.addJobContent("sqoop.args.num.mappers", "1")
.build()
}
参数 | key | 说明 |
---|---|---|
sqoop.mode | import/export/… | |
-Dmapreduce.job.queuename | sqoop.env.mapreduce.job.queuename | |
—connect <jdbc-uri> | sqoop.args.connect | Specify JDBC connect string |
—connection-manager <class-name> | sqoop.args.connection.manager | Specify connection manager class name |
—connection-param-file <properties-file> | sqoop.args.connection.param.file | Specify connection parameters file |
—driver <class-name> | sqoop.args.driver | Manually specify JDBC driver class to use |
—hadoop-home <hdir> | sqoop.args.hadoop.home | Override $HADOOP_MAPRED_HOME_ARG |
—hadoop-mapred-home <dir> | sqoop.args.hadoop.mapred.home | Override $HADOOP_MAPRED_HOME_ARG |
—help | sqoop.args.help | Print usage instructions |
-P | Read password from console | |
—password <password> | sqoop.args.password | Set authentication password |
—password-alias <password-alias> | sqoop.args.password.alias | Credential provider password alias |
—password-file <password-file> | sqoop.args.password.file | Set authentication password file path |
—relaxed-isolation | sqoop.args.relaxed.isolation | Use read-uncommitted isolation for imports |
—skip-dist-cache | sqoop.args.skip.dist.cache | Skip copying jars to distributed cache |
—username <username> | sqoop.args.username | Set authentication username |
—verbose | sqoop.args.verbose | Print more information while working |
参数 | key | 说明 |
---|---|---|
—batch | sqoop.args.batch | Indicates underlying statements to be executed in batch mode |
—call <arg> | sqoop.args.call | Populate the table using this stored procedure (one call per row) |
—clear-staging-table | sqoop.args.clear.staging.table | Indicates that any data in staging table can be deleted |
—columns <col,col,col…> | sqoop.args.columns | Columns to export to table |
—direct | sqoop.args.direct | Use direct export fast path |
—export-dir <dir> | sqoop.args.export.dir | HDFS source path for the export |
-m,—num-mappers <n> | sqoop.args.num.mappers | Use ‘n’ map tasks to export in parallel |
—mapreduce-job-name <name> | sqoop.args.mapreduce.job.name | Set name for generated mapreduce job |
—staging-table <table-name> | sqoop.args.staging.table | Intermediate staging table |
—table <table-name> | sqoop.args.table | Table to populate |
—update-key <key> | sqoop.args.update.key | Update records by specified key column |
—update-mode <mode> | sqoop.args.update.mode | Specifies how updates are performed when new rows are found with non-matching keys in database |
—validate | sqoop.args.validate | Validate the copy using the configured validator |
—validation-failurehandler <validation-failurehandler> | sqoop.args.validation.failurehandler | Validate the copy using the configured validator |
—validation-threshold <validation-threshold> | sqoop.args.validation.threshold | Fully qualified class name for ValidationThreshold |
—validator <validator> | sqoop.args.validator | Fully qualified class name for the Validator |
参数 | key | 说明 |
---|---|---|
—append | sqoop.args.append | Imports data in append mode |
—as-avrodatafile | sqoop.args.as.avrodatafile | Imports data to Avro data files |
—as-parquetfile | sqoop.args.as.parquetfile | Imports data to Parquet files |
—as-sequencefile | sqoop.args.as.sequencefile | Imports data to SequenceFiles |
—as-textfile | sqoop.args.as.textfile | Imports data as plain text (default) |
—autoreset-to-one-mapper | sqoop.args.autoreset.to.one.mapper | Reset the number of mappers to one mapper if no split key available |
—boundary-query <statement> | sqoop.args.boundary.query | Set boundary query for retrieving max and min value of the primary key |
—case-insensitive | sqoop.args.case.insensitive | Data Base is case insensitive, split where condition transfrom to lower case! |
—columns <col,col,col…> | sqoop.args.columns | Columns to import from table |
—compression-codec <codec> | sqoop.args.compression.codec | Compression codec to use for import |
—delete-target-dir | sqoop.args.delete.target.dir | Imports data in delete mode |
—direct | sqoop.args.direct | Use direct import fast path |
—direct-split-size <n> | sqoop.args.direct.split.size | Split the input stream every ‘n’ bytes when importing in direct mode |
-e,—query <statement> | sqoop.args.query | Import results of SQL ‘statement’ |
—fetch-size <n> | sqoop.args.fetch.size | Set number ‘n’ of rows to fetch from the database when more rows are needed |
—inline-lob-limit <n> | sqoop.args.inline.lob.limit | Set the maximum size for an inline LOB |
-m,—num-mappers <n> | sqoop.args.num.mappers | Use ‘n’ map tasks to import in parallel |
—mapreduce-job-name <name> | sqoop.args.mapreduce.job.name | Set name for generated mapreduce job |
—merge-key <column> | sqoop.args.merge.key | Key column to use to join results |
—split-by <column-name> | sqoop.args.split.by | Column of the table used to split work units |
—table <table-name> | sqoop.args.table | Table to read |
—target-dir <dir> | sqoop.args.target.dir | HDFS plain table destination |
—validate | sqoop.args.validate | Validate the copy using the configured validator |
—validation-failurehandler <validation-failurehandler> | sqoop.args.validation.failurehandler | Fully qualified class name for ValidationFa ilureHandler |
—validation-threshold <validation-threshold> | sqoop.args.validation.threshold | Fully qualified class name for ValidationTh reshold |
—validator <validator> | sqoop.args.validator | Fully qualified class name for the Validator |
—warehouse-dir <dir> | sqoop.args.warehouse.dir | HDFS parent for table destination |
—where <where clause> | sqoop.args.where | WHERE clause to use during import |
-z,—compress | sqoop.args.compress | Enable compression |
参数 | key | 说明 |
---|---|---|
—check-column <column> | sqoop.args.check.column | Source column to check for incremental change |
—incremental <import-type> | sqoop.args.incremental | Define an incremental import of type ‘append’ or ‘lastmodified’ |
—last-value <value> | sqoop.args.last.value | Last imported value in the incremental check column |
参数 | key | 说明 |
---|---|---|
—enclosed-by <char> | sqoop.args.enclosed.by | Sets a required field enclosing character |
—escaped-by <char> | sqoop.args.escaped.by | Sets the escape character |
—fields-terminated-by <char> | sqoop.args.fields.terminated.by | Sets the field separator character |
—lines-terminated-by <char> | sqoop.args.lines.terminated.by | Sets the end-of-line character |
—mysql-delimiters | sqoop.args.mysql.delimiters | Uses MySQL’s default delimiter set: fields: , lines: \n escaped-by: \ optionally-enclosed-by: ‘ |
—optionally-enclosed-by <char> | sqoop.args.optionally.enclosed.by | Sets a field enclosing character |
参数 | key | 说明 |
---|---|---|
—input-enclosed-by <char> | sqoop.args.input.enclosed.by | Sets a required field encloser |
—input-escaped-by <char> | sqoop.args.input.escaped.by | Sets the input escape character |
—input-fields-terminated-by <char> | sqoop.args.input.fields.terminated.by | Sets the input field separator |
—input-lines-terminated-by <char> | sqoop.args.input.lines.terminated.by | Sets the input end-of-line char |
—input-optionally-enclosed-by <char> | sqoop.args.input.optionally.enclosed.by | Sets a field enclosing character |
参数 | key | 说明 |
---|---|---|
—create-hive-table | sqoop.args.create.hive.table | Fail if the target hive table exists |
—hive-database <database-name> | sqoop.args.hive.database | Sets the database name to use when importing to hive |
—hive-delims-replacement <arg> | sqoop.args.hive.delims.replacement | Replace Hive record \0x01 and row delimiters (\n\r) from imported string fields with user-defined string |
—hive-drop-import-delims | sqoop.args.hive.drop.import.delims | Drop Hive record \0x01 and row delimiters (\n\r) from imported string fields |
—hive-home <dir> | sqoop.args.hive.home | Override $HIVE_HOME |
—hive-import | sqoop.args.hive.import | Import tables into Hive (Uses Hive’s default delimiters if none are set.) |
—hive-overwrite | sqoop.args.hive.overwrite | Overwrite existing data in the Hive table |
—hive-partition-key <partition-key> | sqoop.args.hive.partition.key | Sets the partition key to use when importing to hive |
—hive-partition-value <partition-value> | sqoop.args.hive.partition.value | Sets the partition value to use when importing to hive |
—hive-table <table-name> | sqoop.args.hive.table | Sets the table name to use when importing to hive |
—map-column-hive <arg> | sqoop.args.map.column.hive | Override mapping for specific column to hive types. |
参数 | key | 说明 |
---|---|---|
—column-family <family> | sqoop.args.column.family | Sets the target column family for the import |
—hbase-bulkload | sqoop.args.hbase.bulkload | Enables HBase bulk loading |
—hbase-create-table | sqoop.args.hbase.create.table | If specified, create missing HBase tables |
—hbase-row-key <col> | sqoop.args.hbase.row.key | Specifies which input column to use as the row key |
—hbase-table <table> | sqoop.args.hbase.table | Import to <table>in HBase |
参数 | key | 说明 |
---|---|---|
—hcatalog-database <arg> | sqoop.args.hcatalog.database | HCatalog database name |
—hcatalog-home <hdir> | sqoop.args.hcatalog.home | Override $HCAT_HOME |
—hcatalog-partition-keys <partition-key> | sqoop.args.hcatalog.partition.keys | Sets the partition keys to use when importing to hive |
—hcatalog-partition-values <partition-value> | sqoop.args.hcatalog.partition.values | Sets the partition values to use when importing to hive |
—hcatalog-table <arg> | sqoop.args.hcatalog.table | HCatalog table name |
—hive-home <dir> | sqoop.args.hive.home | Override $HIVE_HOME |
—hive-partition-key <partition-key> | sqoop.args.hive.partition.key | Sets the partition key to use when importing to hive |
—hive-partition-value <partition-value> | sqoop.args.hive.partition.value | Sets the partition value to use when importing to hive |
—map-column-hive <arg> | sqoop.args.map.column.hive | Override mapping for specific column to hive types. |
HCatalog import specific options: | ||
—create-hcatalog-table | sqoop.args.create.hcatalog.table | Create HCatalog before import |
—hcatalog-storage-stanza <arg> | sqoop.args.hcatalog.storage.stanza | HCatalog storage stanza for table creation |
参数 | key | 说明 |
---|---|---|
—accumulo-batch-size <size> | sqoop.args.accumulo.batch.size | Batch size in bytes |
—accumulo-column-family <family> | sqoop.args.accumulo.column.family | Sets the target column family for the import |
—accumulo-create-table | sqoop.args.accumulo.create.table | If specified, create missing Accumulo tables |
—accumulo-instance <instance> | sqoop.args.accumulo.instance | Accumulo instance name. |
—accumulo-max-latency <latency> | sqoop.args.accumulo.max.latency | Max write latency in milliseconds |
—accumulo-password <password> | sqoop.args.accumulo.password | Accumulo password. |
—accumulo-row-key <col> | sqoop.args.accumulo.row.key | Specifies which input column to use as the row key |
—accumulo-table <table> | sqoop.args.accumulo.table | Import to <table>in Accumulo |
—accumulo-user <user> | sqoop.args.accumulo.user | Accumulo user name. |
—accumulo-visibility <vis> | sqoop.args.accumulo.visibility | Visibility token to be applied to all rows imported |
—accumulo-zookeepers <zookeepers> | sqoop.args.accumulo.zookeepers | Comma-separated list of zookeepers (host:port) |
参数 | key | 说明 |
---|---|---|
—bindir <dir> | sqoop.args.bindir | Output directory for compiled objects |
—class-name <name> | sqoop.args.class.name | Sets the generated class name. This overrides —package-name. When combined with —jar-file, sets the input class. |
—input-null-non-string <null-str> | sqoop.args.input.null.non.string | Input null non-string representation |
—input-null-string <null-str> | sqoop.args.input.null.string | Input null string representation |
—jar-file <file> | sqoop.args.jar.file | Disable code generation; use specified jar |
—map-column-java <arg> | sqoop.args.map.column.java | Override mapping for specific columns to java types |
—null-non-string <null-str> | sqoop.args.null.non.string | Null non-string representation |
—null-string <null-str> | sqoop.args.null.string | Null string representation |
—outdir <dir> | sqoop.args.outdir | Output directory for generated code |
—package-name <name> | sqoop.args.package.name | Put auto-generated classes in this package |
must preceed any tool-specific arguments,Generic options supported are
参数 | key | 说明 |
---|---|---|
-conf <configuration file> | sqoop.args.conf | specify an application configuration file |
-D <property=value> | sqoop.args.D | use value for given property |
-fs <local | namenode:port> | sqoop.args.fs |
-jt <local | resourcemanager:port> | sqoop.args.jt |
-files <comma separated list of files> | sqoop.args.files | specify comma separated files to be copied to the map reduce cluster |
-libjars <comma separated list of jars> | sqoop.args.libjars | specify comma separated jar files to include in the classpath. |
-archives <comma separated list of archives> | sqoop.args.archives | specify comma separated archives to be unarchived on the compute machines. |