Apache Zeppelin 整合 Spark 和 Hudi

一 环境信息

1.1 组件版本

组件 版本
Spark 3.2.3
Hudi 0.14.0
Zeppelin 0.11.0-SNAPSHOT

1.2 环境准备

  1. Zeppelin 整合 Spark 参考:Apache Zeppelin 一文打尽
  2. Hudi0.14.0编译参考:Hudi0.14.0 最新编译

二 整合 Spark 和 Hudi

2.1 配置

shell 复制代码
%spark.conf

SPARK_HOME /usr/lib/spark

# set execution mode
spark.master yarn
spark.submit.deployMode client

# --jars
spark.jars /root/app/jars/hudi-spark3.2-bundle_2.12-0.14.0.jar

# --conf
spark.serializer org.apache.spark.serializer.KryoSerializer
spark.sql.catalog.spark_catalog org.apache.spark.sql.hudi.catalog.HoodieCatalog
spark.sql.extensions org.apache.spark.sql.hudi.HoodieSparkSessionExtension
spark.kryo.registrator org.apache.spark.HoodieSparkKryoRegistrar

Specifying yarn-client & yarn-cluster in spark.master is not supported in Spark 3.x any more, instead you need to use spark.master and spark.submit.deployMode together.

Mode spark.master spark.submit.deployMode
Yarn Client yarn client
Yarn Cluster yarn cluster

2.2 导入依赖

scala 复制代码
%spark
import scala.collection.JavaConversions._
import org.apache.spark.sql.SaveMode._
import org.apache.hudi.DataSourceReadOptions._
import org.apache.hudi.DataSourceWriteOptions._
import org.apache.hudi.common.table.HoodieTableConfig._
import org.apache.hudi.config.HoodieWriteConfig._
import org.apache.hudi.keygen.constant.KeyGeneratorOptions._
import org.apache.hudi.common.model.HoodieRecord
import spark.implicits._

2.3 插入数据

scala 复制代码
%spark
val tableName = "trips_table"
val basePath = "hdfs:///tmp/trips_table"
val columns = Seq("ts","uuid","rider","driver","fare","city")
val data =
  Seq((1695159649087L,"334e26e9-8355-45cc-97c6-c31daf0df330","rider-A","driver-K",19.10,"san_francisco"),
    (1695091554788L,"e96c4396-3fad-413a-a942-4cb36106d721","rider-C","driver-M",27.70 ,"san_francisco"),
    (1695046462179L,"9909a8b1-2d15-4d3d-8ec9-efc48c536a00","rider-D","driver-L",33.90 ,"san_francisco"),
    (1695516137016L,"e3cf430c-889d-4015-bc98-59bdce1e530c","rider-F","driver-P",34.15,"sao_paulo"    ),
    (1695115999911L,"c8abbe79-8d89-47ea-b4ce-4d224bae5bfa","rider-J","driver-T",17.85,"chennai"));

var inserts = spark.createDataFrame(data).toDF(columns:_*)
inserts.write.format("hudi").
  option(PARTITIONPATH_FIELD_NAME.key(), "city").
  option(TABLE_NAME, tableName).
  mode(Overwrite).
  save(basePath)

2.3 查询数据

scala 复制代码
%spark
val tripsDF = spark.read.format("hudi").load(basePath)
tripsDF.createOrReplaceTempView("trips_table")
spark.sql("SELECT uuid, fare, ts, rider, driver, city FROM  trips_table WHERE fare > 20.0").show()

结果:

shell 复制代码
+--------------------+-----+-------------+-------+--------+-------------+
|                uuid| fare|           ts|  rider|  driver|         city|
+--------------------+-----+-------------+-------+--------+-------------+
|e96c4396-3fad-413...| 27.7|1695091554788|rider-C|driver-M|san_francisco|
|9909a8b1-2d15-4d3...| 33.9|1695046462179|rider-D|driver-L|san_francisco|
|e3cf430c-889d-401...|34.15|1695516137016|rider-F|driver-P|    sao_paulo|
+--------------------+-----+-------------+-------+--------+-------------+

相关推荐
EasyDSS2 分钟前
视频监控从安装到优化的技术指南,视频汇聚系统EasyCVR智能安防系统构建之道
大数据·网络·网络协议·音视频
lilye6624 分钟前
精益数据分析(20/126):解析经典数据分析框架,助力创业增长
大数据·人工智能·数据分析
苏小夕夕37 分钟前
spark-streaming(二)
大数据·spark·kafka
珈和info40 分钟前
珈和科技助力“农险提效200%”!“遥感+”技术创新融合省级示范项目荣登《湖北卫视》!
大数据·科技·无人机·智慧农业
盈达科技44 分钟前
盈达科技:登顶GEO优化全球制高点,以AICC定义AI时代内容智能优化新标杆
大数据·人工智能
电商数据girl2 小时前
产品经理对于电商接口的梳理||电商接口文档梳理与接入
大数据·数据库·python·自动化·产品经理
敖云岚3 小时前
【AI】SpringAI 第五弹:接入千帆大模型
java·大数据·人工智能·spring boot·后端
宅小海3 小时前
spark和Hadoop的区别和联系
大数据·hadoop·spark
root666/3 小时前
【大数据技术-联邦集群RBF】DFSRouter日志一直打印修改Membership为EXPIRED状态的日志分析
java·大数据·hadoop
shichaog3 小时前
语音合成之一TTS技术发展史综述
spark·语音合成·tts·端到端