本文主要介绍在DLA中如何快速上手时序时空引擎Ganos。

操作步骤

  1. 准备数据
    将tiff文件上传至OSS指定目录下，例如：
    oss://bucket名称/raster
  2. 加载OSS数据
    1. 新建maven工程dla-ganos-quickstart，然后编辑项目的pom.xml文件：
      <?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">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.aliyun.ganos.dla</groupId>
    <artifactId>dla-ganos-quickstart</artifactId>
    <version>1.0</version>
    <properties>
        <scala.version>2.11.12</scala.version>
        <scala.binary.version>2.11</scala.binary.version>
        <scala.xml.version>1.0.6</scala.xml.version>
        <scala.parsers.version>1.0.6</scala.parsers.version>
        <scalalogging.version>3.8.0</scalalogging.version>
        <spark.version>2.4.3</spark.version>
        <kryo.version>3.0.3</kryo.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>com.aliyun.ganos</groupId>
            <artifactId>dla-ganos-sdk</artifactId>
            <version>1.0</version>
            <scope>system</scope>
            <systemPath>
                下载的dla-ganos-sdk-1.0.jar的路径
            </systemPath>
        </dependency>
        <dependency>    
            <groupId>io.spray</groupId>    
            <artifactId>spray-json_2.11</artifactId>    
            <version>1.3.5</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_${scala.binary.version}</artifactId>
            <exclusions>
                <exclusion>
                    <groupId>com.fasterxml.jackson.core</groupId>
                    <artifactId>jackson-databind</artifactId>
                </exclusion>
            </exclusions>
            <version>${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-catalyst_${scala.binary.version}</artifactId>
            <version>${spark.version}</version>
            <scope>provided</scope>
        </dependency>
         <!-- GeoTools -->
        <dependency>
            <groupId>org.geotools</groupId>
            <artifactId>gt-geojson</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>org.geotools</groupId>
            <artifactId>gt-metadata</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>org.geotools</groupId>
            <artifactId>gt-referencing</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>org.geotools.jdbc</groupId>
            <artifactId>gt-jdbc-postgis</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>org.geotools</groupId>
            <artifactId>gt-epsg-hsql</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>com.aliyun.oss</groupId>
            <artifactId>aliyun-sdk-oss</artifactId>
            <version>3.9.0</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <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>
                <configuration>
                    <compilerPlugins>
                        <compilerPlugin>
                            <groupId>org.spire-math</groupId>
                            <artifactId>kind-projector_2.11</artifactId>
                            <version>0.9.4</version>
                        </compilerPlugin>
                    </compilerPlugins>
                </configuration>
            </plugin>
        </plugins>
    </build>
     <repositories>
        <repository>
            <id>osgeo</id>
            <name>OSGeo Release Repository</name>
            <url>https://repo.osgeo.org/repository/release/</url>
            <snapshots><enabled>false</enabled></snapshots>
            <releases><enabled>true</enabled></releases>
        </repository>
        <repository>
            <id>osgeo-snapshot</id>
            <name>OSGeo Snapshot Repository</name>
            <url>https://repo.osgeo.org/repository/snapshot/</url>
            <snapshots><enabled>true</enabled></snapshots>
            <releases><enabled>false</enabled></releases>
        </repository>
    </repositories>
</project>
    2. 创建scala文件OSSTest.scala：
      import com.aliyun.ganos.dla._
import com.aliyun.ganos.dla.raster._
import com.aliyun.ganos.dla.oss._
import com.aliyun.ganos.dla.geometry._
import com.typesafe.config.ConfigFactory
import org.apache.log4j.{Level, Logger}
import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession

object OSSTest extends App {

  Logger.getLogger("org").setLevel(Level.ERROR)
  Logger.getLogger("com").setLevel(Level.ERROR)
  val spark: SparkSession = {
    val session = SparkSession.builder
      .withKryoSerialization
      .config(additionalConf)
      .getOrCreate()
    session
  }

  spark.withGanosGeometry
  spark.withGanosRaster

  val uri = new java.net.URI("oss://bucket名称/raster") //指定文件夹路径

  val options = Map(
    "crs"->"EPSG:4326",
    "endpoint" -> "EndPoint地址",
    "accessKeyId" -> "用户AccessKeyID",
    "accessKeySecret" -> "用户AccessKeySecret")
  
  val rf = spark.read.ganos.oss(options).loadLayer(uri)
  rf.show
  def additionalConf = new SparkConf(false)
}
    3. 进行编译工程：
      mvn clean package
  3. 提交作业

    登录Data Lake Analytics管理控制台提交Spark作业，详情请参见：创建和执行Spark作业。

    保存运行成功后查看作业状态，可以看到原始tiff以Tile的形式加载到Spark中，然后您就可以对这些Tile进行相关操作了。dla_ganos_quickstart_1