安装geomesa-hbase
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版本：geomesa-hbase_2.11-3.4.0-bin.tar.gz
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解压到指定目录后为其添加环境变量
export GEOMESA_HBASE_HOME=/home/hadoop/geomesa-hbase_2.11-3.4.0 export PATH=$PATH:$GEOMESA_HBASE_HOME/bin
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部署GeoMesa-HBase分布式运行jar
geomesa-hbase需要使用本地过滤器来加速查询，因此需要将GeoMesa的runtime JAR包，拷贝到HBase的库目录下。
cp ./dist/hbase/geomesa-hbase-distributed-runtime-hbase1_2.11-3.4.0.jar /home/hadoop/hbase/lib/ -
注册协处理器
GeoMesa利用服务器端处理来加速某些查询。具体实现：
在HBase的配置文件hbase-site.xml添加如下内容：
<property> <name>hbase.coprocessor.user.region.classes</name> <value>org.locationtech.geomesa.hbase.coprocessor.GeoMesaCoprocessor</value> </property> -
设置命令行工具
将HBase配置文件hbase-site.xml打包进geomesa-hbase-datastore_2.11-$VERSION.jar中：
zip -r lib/geomesa-hbase-datastore_2.11-hbase1_2.11-3.4.0.jar /home/hadoop/hbase/conf/hbase-site.xml
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进入到${GEOMESA_HBASE_HOME},运行：
./bin/install-shapefile-support.sh
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测试是否安装成功
geomesa-hbase version
时空索引
导入数据相关链接：GeoMesa命令行，索引概述_爱是与世界平行-程序员信息网 - 程序员信息网 (i4k.xyz)
导入数据官方链接：8.3. Ingest Commands — GeoMesa 3.2.2 Manuals
定义特征类型官方链接：[8.6. Defining Simple Feature Types — GeoMesa 3.2.2 Manuals](https://www.geomesa.org/documentation/3.2.2/user/cli/sfts.html#cli-sft-conf)
转换器官方链接：9. GeoMesa Convert — GeoMesa 3.2.2 Manuals
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数据准备
在${GEOMESA_HBASE_HOME}下新建data目录，进入data目录创建data.csv文件
AAA,red,113.918417,22.505892,2017-04-09T18:03:46 BBB,white,113.960719,22.556511,2017-04-24T07:38:47 CCC,blue,114.088333,22.637222,2017-04-23T15:07:54 DDD,yellow,114.195456,22.596103,2017-04-21T21:27:06 EEE,black,113.897614,22.551331,2017-04-09T09:34:48 -
定义特征类型
geomesa = { sfts = { example = { type-name = "example" attributes = [ { name = "carid", type = "String", index = true } { name = "color", type = "String", index = false } { name = "double_0", type = "Double", index = false } { name = "double_1", type = "Double", index = false } { name = "time", type = "Date", index = false } { name = "geom", type = "Point", index = true,srid = 4326,default = true } ] } } } -
定义转换器
geomesa.converters.example = { "fields" : [ { "name" : "carid", "transform" : "toString($1)" }, { "name" : "color", "transform" : "toString($2)" }, { "name" : "double_0", "transform" : "toDouble($3)" }, { "name" : "double_1", "transform" : "toDouble($4)" }, { "name" : "time", "transform" : "isoDateTime($5)" }, { "name" : "geom", "transform" : "point($double_0,$double_1)" } ], "format" : "CSV", "id-field" : "md5(string2bytes($0))", "options" : { "encoding" : "UTF-8", "error-mode" : "skip-bad-records", "parse-mode" : "incremental", "validators" : [ "index" ] }, "type" : "delimited-text" } -
导入数据
geomesa-hbase ingest --catalog geomesa01 \ --feature-name cars20 \ --input-format csv \ -C conf/testconvertor.convert \ -s conf/myschema.sft \ "data/data.csv"
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进入hbase shell查看导入的数据
Z2/Z3指示了Geomesa的索引方式（Z2：空间索引；Z3：时空索引）
索引官方链接：7.3. Index Basics — GeoMesa 3.2.2 Manuals
scan 'geomesa01_cars20_z3_geom_time_v7'
KNN查询
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将GeoSparkModified解压到指定目录，此处为 /home/hadoop/compress/
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使用geospark.jar作为依赖项运行Spark shell
spark-shell --jars /home/hadoop/compress/GeoSparkModified-master/classes/artifacts/geospark_jar/geospark.jar
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导包运行KNN查询代码
/home/hadoop/compress/GeoSparkModified-master/src/test/resources/arealm.csv文件中含有121960条经纬度
import org.datasyslab.geospark.spatialOperator.KNNQuery import org.datasyslab.geospark.spatialRDD.PointRDD; import com.vividsolutions.jts.geom.GeometryFactory; import com.vividsolutions.jts.geom.Point; import com.vividsolutions.jts.geom.Coordinate; val fact=new GeometryFactory(); val queryPoint=fact.createPoint(new Coordinate(-109.73, 35.08)); //查询点 val objectRDD = new PointRDD(sc, "file:///home/hadoop/compress/GeoSparkModified-master/src/test/resources/arealm.csv", 0, "csv"); val resultSize = KNNQuery.SpatialKnnQuery(objectRDD, queryPoint, 5); //查询邻近查询点的5个点
