我尝试使用 Apache Spark 阅读DynamodDB
表。
以下是我的实施:
所以在Spark Shell中
spark-shell --jars /usr/share/aws/emr/ddb/lib/emr-ddb-hadoop.jar
import org.apache.hadoop.io.Text;
import org.apache.hadoop.dynamodb.DynamoDBItemWritable
/* Importing DynamoDBInputFormat and DynamoDBOutputFormat */
import org.apache.hadoop.dynamodb.read.DynamoDBInputFormat
import org.apache.hadoop.dynamodb.write.DynamoDBOutputFormat
import org.apache.hadoop.mapred.JobConf
import org.apache.hadoop.io.LongWritable
var jobConf = new JobConf(sc.hadoopConfiguration)
jobConf.set("dynamodb.servicename", "dynamodb")
jobConf.set("dynamodb.input.tableName", "myDynamoDBTable")
// Pointing to DynamoDB table
jobConf.set("dynamodb.endpoint", "dynamodb.us-east-1.amazonaws.com")
jobConf.set("dynamodb.regionid", "us-east-1") jobConf.set("dynamodb.throughput.read", "1")
jobConf.set("dynamodb.throughput.read.percent", "1")
jobConf.set("dynamodb.version", "2011-12-05")
jobConf.set("mapred.output.format.class", "org.apache.hadoop.dynamodb.write.DynamoDBOutputFormat")
jobConf.set("mapred.input.format.class", "org.apache.hadoop.dynamodb.read.DynamoDBInputFormat")
var orders = sc.hadoopRDD(jobConf, classOf[DynamoDBInputFormat], classOf[Text], classOf[DynamoDBItemWritable])
我们得到的结果是"命令"变量
如何将此结果转换为 Parquet文件或格式?
更新:我发现这段代码可以访问和转换dynamodb数据 https://github.com/onzocom/spark-dynamodb/blob/master/src/main/scala/com/onzo/spark/dynamodb/DynamoDbRelation.scala?
答案 0 :(得分:1)
数据框可以保存为Parquet文件,但RDD不能。这是因为Parquet文件需要架构。 RDD并不需要拥有架构,但数据框必须。