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【慕课网实战】九、以慕课网日志分析为例 进入大数据 Spark SQL 的世界

即席查询
普通查询

Load Data
1) RDD DataFrame/Dataset
2) Local Cloud(HDFS/S3)

将数据加载成RDD
val masterLog = sc.textFile("file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/logs/spark-hadoop-org.apache.spark.deploy.master.Master-1-hadoop001.out")
val workerLog = sc.textFile("file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/logs/spark-hadoop-org.apache.spark.deploy.worker.Worker-1-hadoop001.out")
val allLog = sc.textFile("file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/logs/*out*")

masterLog.count
workerLog.count
allLog.count

存在的问题:使用使用SQL进行查询呢?

import org.apache.spark.sql.Row
val masterRDD = masterLog.map(x => Row(x))
import org.apache.spark.sql.types._
val schemaString = "line"

val fields = schemaString.split(" ").map(fieldName => StructField(fieldName, StringType, nullable = true))
val schema = StructType(fields)

val masterDF = spark.createDataFrame(masterRDD, schema)
masterDF.show

JSON/Parquet
val usersDF = spark.read.format("parquet").load("file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/examples/src/main/resources/users.parquet")
usersDF.show

spark.sql("select * from parquet.`file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/examples/src/main/resources/users.parquet`").show

Drill 大数据处理框架

从Cloud读取数据: HDFS/S3
val hdfsRDD = sc.textFile("hdfs://path/file")
val s3RDD = sc.textFile("s3a://bucket/object")
s3a/s3n

spark.read.format("text").load("hdfs://path/file")
spark.read.format("text").load("s3a://bucket/object")

val df=spark.read.format("json").load("file:///home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/examples/src/main/resources/people.json")

df.show

TPC-DS

spark-packages.org

posted on 2018-03-02 16:08  旷课小王子  阅读(203)  评论(0编辑  收藏  举报