[Spark][python]以DataFrame方式打开Json文件的例子-低调大师

[Spark][python]以DataFrame方式打开Json文件的例子

2017-12-19 682

[Spark][python]以DataFrame方式打开Json文件的例子：

[training@localhost ~]$ cat people.json
{"name":"Alice","pcode":"94304"}
{"name":"Brayden","age":30,"pcode":"94304"}
{"name":"Carla","age":19,"pcoe":"10036"}
{"name":"Diana","age":46}
{"name":"Etienne","pcode":"94104"}
[training@localhost ~]$

[training@localhost ~]$ hdfs dfs -put people.json

[training@localhost ~]$ hdfs dfs -cat people.json
{"name":"Alice","pcode":"94304"}
{"name":"Brayden","age":30,"pcode":"94304"}
{"name":"Carla","age":19,"pcoe":"10036"}
{"name":"Diana","age":46}
{"name":"Etienne","pcode":"94104"}

In [1]: sqlContext = HiveContext(sc)

In [2]: peopleDF = sqlContext.read.json("people.json")

17/10/01 05:20:22 INFO hive.HiveContext: Initializing execution hive, version 1.1.0
17/10/01 05:20:22 INFO client.ClientWrapper: Inspected Hadoop version: 2.6.0-cdh5.7.0
17/10/01 05:20:22 INFO client.ClientWrapper: Loaded org.apache.hadoop.hive.shims.Hadoop23Shims for Hadoop version 2.6.0-cdh5.7.0
17/10/01 05:20:23 INFO hive.metastore: Trying to connect to metastore with URI thrift://localhost.localdomain:9083
17/10/01 05:20:23 INFO hive.metastore: Opened a connection to metastore, current connections: 1
17/10/01 05:20:23 INFO hive.metastore: Connected to metastore.
17/10/01 05:20:23 INFO session.SessionState: Created HDFS directory: file:/tmp/spark-839b35f5-91a1-436c-aae5-922ebacb27f1/scratch/training
17/10/01 05:20:23 INFO session.SessionState: Created local directory: /tmp/b3e52bfc-fe3a-4abe-ac7b-da071104b2f9_resources
17/10/01 05:20:23 INFO session.SessionState: Created HDFS directory: file:/tmp/spark-839b35f5-91a1-436c-aae5-922ebacb27f1/scratch/training/b3e52bfc-fe3a-4abe-ac7b-da071104b2f9
17/10/01 05:20:23 INFO session.SessionState: Created local directory: /tmp/training/b3e52bfc-fe3a-4abe-ac7b-da071104b2f9
17/10/01 05:20:23 INFO session.SessionState: Created HDFS directory: file:/tmp/spark-839b35f5-91a1-436c-aae5-922ebacb27f1/scratch/training/b3e52bfc-fe3a-4abe-ac7b-da071104b2f9/_tmp_space.db
17/10/01 05:20:23 INFO session.SessionState: No Tez session required at this point. hive.execution.engine=mr.
17/10/01 05:20:23 INFO json.JSONRelation: Listing hdfs://localhost:8020/user/training/people.json on driver
17/10/01 05:20:25 INFO storage.MemoryStore: Block broadcast_0 stored as values in memory (estimated size 251.1 KB, free 251.1 KB)
17/10/01 05:20:25 INFO storage.MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 21.6 KB, free 272.7 KB)
17/10/01 05:20:25 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on localhost:42171 (size: 21.6 KB, free: 208.8 MB)
17/10/01 05:20:25 INFO spark.SparkContext: Created broadcast 0 from json at NativeMethodAccessorImpl.java:-2
17/10/01 05:20:26 INFO mapred.FileInputFormat: Total input paths to process : 1
17/10/01 05:20:26 INFO spark.SparkContext: Starting job: json at NativeMethodAccessorImpl.java:-2
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Got job 0 (json at NativeMethodAccessorImpl.java:-2) with 1 output partitions
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Final stage: ResultStage 0 (json at NativeMethodAccessorImpl.java:-2)
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Parents of final stage: List()
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Missing parents: List()
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[3] at json at NativeMethodAccessorImpl.java:-2), which has no missing parents
17/10/01 05:20:26 INFO storage.MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.3 KB, free 277.1 KB)
17/10/01 05:20:26 INFO storage.MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.4 KB, free 279.5 KB)
17/10/01 05:20:26 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on localhost:42171 (size: 2.4 KB, free: 208.8 MB)
17/10/01 05:20:26 INFO spark.SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006
17/10/01 05:20:26 INFO scheduler.DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[3] at json at NativeMethodAccessorImpl.java:-2)
17/10/01 05:20:26 INFO scheduler.TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
17/10/01 05:20:26 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, partition 0,PROCESS_LOCAL, 2149 bytes)
17/10/01 05:20:26 INFO executor.Executor: Running task 0.0 in stage 0.0 (TID 0)
17/10/01 05:20:26 INFO rdd.HadoopRDD: Input split: hdfs://localhost:8020/user/training/people.json:0+179
17/10/01 05:20:27 INFO Configuration.deprecation: mapred.tip.id is deprecated. Instead, use mapreduce.task.id
17/10/01 05:20:27 INFO Configuration.deprecation: mapred.task.id is deprecated. Instead, use mapreduce.task.attempt.id
17/10/01 05:20:27 INFO Configuration.deprecation: mapred.task.is.map is deprecated. Instead, use mapreduce.task.ismap
17/10/01 05:20:27 INFO Configuration.deprecation: mapred.task.partition is deprecated. Instead, use mapreduce.task.partition
17/10/01 05:20:27 INFO Configuration.deprecation: mapred.job.id is deprecated. Instead, use mapreduce.job.id
17/10/01 05:20:27 INFO executor.Executor: Finished task 0.0 in stage 0.0 (TID 0). 2354 bytes result sent to driver
17/10/01 05:20:27 INFO scheduler.DAGScheduler: ResultStage 0 (json at NativeMethodAccessorImpl.java:-2) finished in 0.715 s
17/10/01 05:20:27 INFO scheduler.TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 667 ms on localhost (1/1)
17/10/01 05:20:27 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
17/10/01 05:20:27 INFO scheduler.DAGScheduler: Job 0 finished: json at NativeMethodAccessorImpl.java:-2, took 1.084685 s
17/10/01 05:20:27 INFO hive.HiveContext: default warehouse location is /user/hive/warehouse
17/10/01 05:20:28 INFO hive.HiveContext: Initializing metastore client version 1.1.0 using Spark classes.
17/10/01 05:20:28 INFO client.ClientWrapper: Inspected Hadoop version: 2.6.0-cdh5.7.0
17/10/01 05:20:28 INFO client.ClientWrapper: Loaded org.apache.hadoop.hive.shims.Hadoop23Shims for Hadoop version 2.6.0-cdh5.7.0
17/10/01 05:20:28 INFO storage.BlockManagerInfo: Removed broadcast_1_piece0 on localhost:42171 in memory (size: 2.4 KB, free: 208.8 MB)
17/10/01 05:20:28 INFO spark.ContextCleaner: Cleaned accumulator 2
17/10/01 05:20:30 INFO hive.metastore: Trying to connect to metastore with URI thrift://localhost.localdomain:9083
17/10/01 05:20:30 INFO hive.metastore: Opened a connection to metastore, current connections: 1
17/10/01 05:20:30 INFO hive.metastore: Connected to metastore.
17/10/01 05:20:30 INFO session.SessionState: Created HDFS directory: /tmp/hive/training
17/10/01 05:20:30 INFO session.SessionState: Created local directory: /tmp/8c1eba54-7260-4314-abbf-7b7de85bdf0a_resources
17/10/01 05:20:30 INFO session.SessionState: Created HDFS directory: /tmp/hive/training/8c1eba54-7260-4314-abbf-7b7de85bdf0a
17/10/01 05:20:30 INFO session.SessionState: Created local directory: /tmp/training/8c1eba54-7260-4314-abbf-7b7de85bdf0a
17/10/01 05:20:30 INFO session.SessionState: Created HDFS directory: /tmp/hive/training/8c1eba54-7260-4314-abbf-7b7de85bdf0a/_tmp_space.db
17/10/01 05:20:30 INFO session.SessionState: No Tez session required at this point. hive.execution.engine=mr.

In [3]: type(peopleDF)
Out[3]: pyspark.sql.dataframe.DataFrame

In [4]:

本文转自健哥的数据花园博客园博客，原文链接：http://www.cnblogs.com/gaojian/p/7617731.html，如需转载请自行联系原作者

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原文链接：https://yq.aliyun.com/articles/355125

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[Spark][Hive]Hive的命令行客户端启动：

[Spark][Hive]Hive的命令行客户端启动： [training@localhost Desktop]$ chkconfig | grep hive hive-metastore 0:off 1:off 2:off 3:on 4:on 5:on 6:off hive-server2 0:off 1:off 2:off 3:on 4:on 5:on 6:off [training@localhost Desktop]$ service hive-server2 status Hive Server2 is running [ OK ] [training@localhost Desktop]$ service hive-metastore status Hive Metastore is running [ OK ] [training@localhost Desktop]$ which hive /usr/bin/hive [training@localhost Desktop]$ [training@localhost Desktop]$ hive 2017-10-01 0...

2017-12-19

668

package com.jxd import org.apache.spark.SparkContextimport org.apache.spark.SparkConfimport java.sql.Connectionimport java.sql.DriverManagerobject hello { def main(args: Array[String]): Unit = { var conf = new SparkConf().setAppName("Hello World") var sc = new SparkContext(conf) var input = sc.textFile("test/hello", 2) var count = input.flatMap(name => name.split(" ")).map((_, 1)).reduceByKey(((a, b) => a + b)) count.foreachPartition(insertToMysql) } def insertToMysql(iterator: Iterator[(S...

2017-12-19

514

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