使用GeoMesa实现时空索引并进行KNN查询

安装geomesa-hbase

将geomesa-hbase_2.11-3.4.0-bin.tar.gz上传到xshell
解压geomesa-hbase_2.11-3.4.0-bin.tar.gz

tar -zxvf geomesa-hbase_2.11-3.4.0-bin.tar.gz

配置环境变量

vim .bashrc

添加如下内容：

#geomesa_hbase
export GEOMESA_HBASE_HOME=/home/ZQ/geomesa-hbase_2.11-3.4.0
export PATH=$PATH:$GEOMESA_HBASE_HOME/bin

使环境变量生效

source .bashrc

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

cd geomesa-hbase_2.11-3.4.0/

cp ./dist/hbase/geomesa-hbase-distributed-runtime-hbase1_2.11-3.4.0.jar /home/ZQ/hbase-1.4.13/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：

cd hbase-1.4.13/conf

vim hbase-site.xml

 <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：

cd geomesa-hbase_2.11-3.4.0/

zip -r lib/geomesa-hbase-datastore_2.11-hbase1_2.11-3.4.0.jar /home/ZQ/hbase-1.4.13/conf/hbase-site.xml

进入到${GEOMESA_HBASE_HOME},运行：

./bin/install-shapefile-support.sh

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
导入数据官方链接：8.3. Ingest Commands
定义特征类型官方链接：8.6. Defining Simple Feature Types
转换器官方链接：9. GeoMesa Convert

数据准备

在${GEOMESA_HBASE_HOME}下新建data目录，进入data目录创建data.csv

mkdir data

cd data

vim data.csv

在data.csv中增加如下内容：

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

vim  conf/myschema.sft

在文件中增加如下内容

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

vim conf/testconvertor.convert

在文件中增加如下内容

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

启动HDFS和HBase

start-dfs.sh

start-hbase.sh

geomesa-hbase ingest --catalog geomesa01 --feature-name cars20 --input-format csv -C conf/testconvertor.convert -s conf/myschema.sft "data/data.csv"

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）

hbase shell

list

scan 'geomesa01_cars20_z3_geom_time_v7'

KNN查询

将GeoSparkModified解压到指定目录

unzip GeoSparkModified-master.zip

使用geospark.jar作为依赖项运行Spark shell

spark-shell --jars /home/ZQ/GeoSparkModified-master/classes/artifacts/geospark_jar/geospark.jar

导包运行KNN查询代码
/home/ZQ/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/ZQ/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