spark 读取Geomesa(Hbase)数据
package com.grady.geomesa
import org.apache.hadoop.conf.Configuration
import org.apache.spark.SparkConf
import org.apache.spark.sql.{DataFrame, SparkSession}
import org.geotools.data.Query
import org.locationtech.geomesa.spark.{GeoMesaSpark, GeoMesaSparkKryoRegistrator, SpatialRDD}
import org.locationtech.geomesa.spark.jts._
import scala.collection.JavaConversions._
object SparkReadGeomesa {
val GeomesaCatalog = "gradytest"
val GeomesaCatalogFeature = "student"
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("SparkReadGeomesa")
// 这里序列化配置非常关键，否则spark解析不出来数据
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
conf.set("spark.kryo.registrator", classOf[GeoMesaSparkKryoRegistrator].getName)
val ss = SparkSession.builder().config(conf).getOrCreate().withJTS
// 方法一报错：
// java.lang.ClassNotFoundException: org.locationtech.geomesa.hbase.rpc.filter.CqlTransformFilter
// 可能是环境配置关系
// val dataFrame = readGeomesaData(ss)
// showDataFrame(dataFrame, ss)
// 方法二： ok
val spatialRDD = readGeomesaDataToRDD(ss)
showSpatialRDD(spatialRDD)
ss.stop()
}
/**
* 方法一： 获取dataFrame
* @param ss
* @return
*/
def readGeomesaData(ss: SparkSession): DataFrame = {
val params = Map(
"hbase.zookeepers" -> "10.82.xxx.xx:2181",
"hbase.catalog" -> GeomesaCatalog)
val dataFrame = ss.read
.format("geomesa")
.options(params)
.option("geomesa.feature", GeomesaCatalogFeature)
.load()
dataFrame
}
def showDataFrame(dataFrame: DataFrame, ss: SparkSession): Unit = {
dataFrame.show()
println("-----------------------------------")
dataFrame.createOrReplaceTempView("student")
val sqlQuery = "select * from student"
val resultDataFrame = ss.sql(sqlQuery)
resultDataFrame.show()
}
/**
* 方法二： 获取SpatialRDD
* @param ss
* @return
*/
def readGeomesaDataToRDD(ss: SparkSession): SpatialRDD = {
val params = Map(
"hbase.zookeepers" -> "10.82.xxx.xx:2181",
"hbase.catalog" -> GeomesaCatalog)
val spatialRDDProvider = GeoMesaSpark(params)
val query = new Query(GeomesaCatalogFeature)
val resultRDD = spatialRDDProvider.rdd(new Configuration, ss.sparkContext, params, query)
resultRDD
}
def showSpatialRDD(spatialRDD: SpatialRDD): Unit = {
spatialRDD.collect().foreach(row => {
val geom = row.getAttribute("geom").toString
val name = row.getAttribute("name").toString
println("name:" + name + " geom: " + geom)
})
println("-----------------------------------")
spatialRDD.collect().foreach(println)
}
}pom.xml
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<parent>
<artifactId>spark-practise</artifactId>
<groupId>org.example</groupId>
<version>1.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>geomesa</artifactId>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
<geomesa.version>3.1.0</geomesa.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>${hadoop.version}</version>
</dependency>
<dependency>
<groupId>org.locationtech.geomesa</groupId>
<artifactId>geomesa-hbase-spark-runtime-hbase2_2.12</artifactId>
<version>3.3.0</version>
<exclusions>
<exclusion>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.locationtech.geomesa</groupId>
<artifactId>geomesa-spark-core_2.12</artifactId>
<version>3.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-yarn_${scala.binary.version}</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>
<build>
<resources>
<resource>
<directory>src/main/resources</directory>
<filtering>true</filtering>
</resource>
</resources>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.1</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
<scalaVersion>${scala.version}</scalaVersion>
</configuration>
<executions>
<execution>
<id>scala-compile-first</id>
<phase>process-resources</phase>
<goals>
<goal>add-source</goal>
<goal>compile</goal>
</goals>
</execution>
<execution>
<id>scala-test-compile</id>
<phase>process-test-resources</phase>
<goals>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.2.1</version>
<configuration>
<artifactSet>
<excludes>
<exclude>org.slf4j:*</exclude>
</excludes>
</artifactSet>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<createDependencyReducedPom>false</createDependencyReducedPom>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
</transformers>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>运行：spark-submit --master yarn --driver-memory=2G --class com.grady.geomesa.SparkReadGeomesa /app/data/appdeploy/geomesa-1.0-SNAPSHOT.jar
这里最好是在yarn上执行，因为本地执行可能内存不够而卡住，我就被坑了几次
执行日志：(因为多执行了几遍插入，所以有重复数据)
name:jack geom: POINT (11.1 12.1)
name:Lily geom: POINT (12.1 13.1)
name:jack geom: POINT (11.1 12.1)
name:Lily geom: POINT (12.1 13.1)
name:mike geom: POINT (14.1 15.1)
name:jack geom: POINT (11.1 12.1)
name:Lily geom: POINT (12.1 13.1)
name:mike geom: POINT (14.1 15.1)
name:mike geom: POINT (14.1 15.1)
-----------------------------------
ScalaSimpleFeature:000017ed-e5d1-41f8-ae71-84db58b9478f:POINT (11.1 12.1)|1|jack|15
ScalaSimpleFeature:000017ed-e5d1-41f8-a308-efcee8b70bf9:POINT (12.1 13.1)|2|Lily|16
ScalaSimpleFeature:000017ed-e35c-4d77-a841-b3bcf6faa8ac:POINT (11.1 12.1)|1|jack|15
ScalaSimpleFeature:000017ed-e37a-4e60-9d7f-66988be48234:POINT (12.1 13.1)|2|Lily|16
ScalaSimpleFeature:000017ed-e35c-4e9a-8600-97ed8d92c48b:POINT (14.1 15.1)|3|mike|16
ScalaSimpleFeature:000017ed-e37a-4e60-b90f-93fc81e0ab0e:POINT (11.1 12.1)|1|jack|15
ScalaSimpleFeature:000017ed-e35c-4d77-99e7-c6918a06c008:POINT (12.1 13.1)|2|Lily|16
ScalaSimpleFeature:000017ed-e37a-4ebd-b3a5-a9c7399a635b:POINT (14.1 15.1)|3|mike|16
ScalaSimpleFeature:000017ed-e5d1-4257-a75d-b0e23729542e:POINT (14.1 15.1)|3|mike|16手机扫一扫
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