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Spark高效数据分析03、Spack SQL

红目香薰发表于 2022/07/29 10:27:11 2022/07/29

【摘要】编辑Spark高效数据分析03、Spack SQL📋前言📋💝博客：【红目香薰的博客_CSDN博客-计算机理论,2022年蓝桥杯,MySQL领域博主】💝✍本文由在下【红目香薰】原创，首发于CSDN✍🤗2022年最大愿望：【服务百万技术人次】🤗💝Spark初始环境地址：【Spark高效数据分析01、idea开发环境搭建】💝环境需求环境：win10开发工具：IntelliJ ID...

编辑

Spark高效数据分析03、Spack SQL

📋前言📋

💝博客：【红目香薰的博客_CSDN博客-计算机理论,2022年蓝桥杯,MySQL领域博主】💝

✍本文由在下【红目香薰】原创，首发于CSDN✍

🤗2022年最大愿望：【服务百万技术人次】🤗

💝Spark初始环境地址：【Spark高效数据分析01、idea开发环境搭建】💝

环境需求

环境：win10

开发工具：IntelliJ IDEA 2020.1.3 x64

maven版本：3.0.5

1、修改pom.xml

    <dependencies>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.13</artifactId>
            <version>3.3.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.13</artifactId>
            <version>3.3.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.13</artifactId>
            <version>3.3.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-mllib -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mllib_2.13</artifactId>
            <version>3.3.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-hive -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive_2.13</artifactId>
            <version>3.3.0</version>
        </dependency>
    </dependencies>

修改完一定要刷新一下：

编辑

2、创建测试文件【info.json】，这里不是标准的json，面向行编写的【json】文件

{"name":"娉婷的彩亭", "age":19}
{"name":"静怡的梦莹", "age":20}
{"name":"潇洒的龙姑娘", "age":21}
{"name":"优雅的秋兰", "age":21}
{"name":"玲珑的巧蓉", "age":19}

编辑

别担心报错，可以正常读取的

数据2

{"name":"娉婷的星望", "age":19,"birthday": "2001-05-06 12:00:00","sex":"女"}
{"name":"静怡的雷静", "age":20,"birthday": "1999-05-02 12:00:00","sex":"女"}
{"name":"潇洒的春梦", "age":22,"birthday": "2000-01-06 12:00:00","sex":"女"}
{"name":"优雅的蓉菲", "age":21,"birthday": "2001-06-06 12:00:00","sex":"女"}
{"name":"玲珑的文静", "age":19,"birthday": "2002-05-09 12:00:00","sex":"女"}
{"name":"风雅的晓凤", "age":18,"birthday": "2004-05-09 12:00:00","sex":"女"}

编辑

3、SparkSession

SparkSession 是 Spark 最新的 SQL 查询起始点，实质上是 SQLContext 和 HiveContext 的组合。

val spark = SparkSession.builder()
       .appName("Spark SQL").master("local[*]")
       .getOrCreate()
import spark.implicits._

4、Demo1

package com.item.action

import org.apache.spark.sql.SparkSession
object DemoSparkSQL {
        def main(args: Array[String]) {
               val spark = SparkSession.builder()
                      .appName("Spark SQL").master("local[*]")
                      .getOrCreate()
               import spark.implicits._
               val df = spark.read.json("src/info.json")
//               df.show()//展示所有数据
//               df.filter($"age" >= 20).show()//过滤年龄大于20的
               df.createOrReplaceTempView("info")//创建一个视图
               spark.sql("SELECT * FROM info where age >= 20")//sql数据
                       .show()//展示
               spark.stop()
        }
}

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com.item.action.DemoSparkSQL
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
22/07/18 19:58:22 INFO SparkContext: Running Spark version 3.3.0
22/07/18 19:58:23 INFO ResourceUtils: ==============================================================
22/07/18 19:58:23 INFO ResourceUtils: No custom resources configured for spark.driver.
22/07/18 19:58:23 INFO ResourceUtils: ==============================================================
22/07/18 19:58:23 INFO SparkContext: Submitted application: Spark SQL
22/07/18 19:58:23 INFO ResourceProfile: Default ResourceProfile created, executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: cpus, amount: 1.0)
22/07/18 19:58:23 INFO ResourceProfile: Limiting resource is cpu
22/07/18 19:58:23 INFO ResourceProfileManager: Added ResourceProfile id: 0
22/07/18 19:58:23 INFO SecurityManager: Changing view acls to: Administrator
22/07/18 19:58:23 INFO SecurityManager: Changing modify acls to: Administrator
22/07/18 19:58:23 INFO SecurityManager: Changing view acls groups to:
22/07/18 19:58:23 INFO SecurityManager: Changing modify acls groups to:
22/07/18 19:58:23 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(Administrator); groups with view permissions: Set(); users with modify permissions: Set(Administrator); groups with modify permissions: Set()
22/07/18 19:58:23 INFO Utils: Successfully started service 'sparkDriver' on port 57125.
22/07/18 19:58:23 INFO SparkEnv: Registering MapOutputTracker
22/07/18 19:58:23 INFO SparkEnv: Registering BlockManagerMaster
22/07/18 19:58:23 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
22/07/18 19:58:23 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
22/07/18 19:58:23 INFO SparkEnv: Registering BlockManagerMasterHeartbeat
22/07/18 19:58:23 INFO DiskBlockManager: Created local directory at C:\Users\Administrator\AppData\Local\Temp\blockmgr-bb1c5f1a-9493-481d-b6a5-7bb2105634d2
22/07/18 19:58:23 INFO MemoryStore: MemoryStore started with capacity 898.5 MiB
22/07/18 19:58:23 INFO SparkEnv: Registering OutputCommitCoordinator
22/07/18 19:58:24 INFO Utils: Successfully started service 'SparkUI' on port 4040.
22/07/18 19:58:24 INFO Executor: Starting executor ID driver on host 192.168.15.19
22/07/18 19:58:24 INFO Executor: Starting executor with user classpath (userClassPathFirst = false): ''
22/07/18 19:58:24 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 57168.
22/07/18 19:58:24 INFO NettyBlockTransferService: Server created on 192.168.15.19:57168
22/07/18 19:58:24 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
22/07/18 19:58:24 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.15.19, 57168, None)
22/07/18 19:58:24 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.15.19:57168 with 898.5 MiB RAM, BlockManagerId(driver, 192.168.15.19, 57168, None)
22/07/18 19:58:24 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.15.19, 57168, None)
22/07/18 19:58:24 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.15.19, 57168, None)
22/07/18 19:58:24 INFO SharedState: Setting hive.metastore.warehouse.dir ('null') to the value of spark.sql.warehouse.dir.
22/07/18 19:58:24 INFO SharedState: Warehouse path is 'file:/C:/Users/Administrator/IdeaProjects/baidu1/spark-warehouse'.
22/07/18 19:58:25 INFO InMemoryFileIndex: It took 25 ms to list leaf files for 1 paths.
22/07/18 19:58:25 INFO InMemoryFileIndex: It took 1 ms to list leaf files for 1 paths.
22/07/18 19:58:27 INFO FileSourceStrategy: Pushed Filters:
22/07/18 19:58:27 INFO FileSourceStrategy: Post-Scan Filters:
22/07/18 19:58:27 INFO FileSourceStrategy: Output Data Schema: struct<value: string>
22/07/18 19:58:27 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 348.6 KiB, free 898.2 MiB)
22/07/18 19:58:27 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 33.7 KiB, free 898.1 MiB)
22/07/18 19:58:27 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.15.19:57168 (size: 33.7 KiB, free: 898.5 MiB)
22/07/18 19:58:27 INFO SparkContext: Created broadcast 0 from json at DemoSparkSQL.scala:10
22/07/18 19:58:27 INFO FileSourceScanExec: Planning scan with bin packing, max size: 4194304 bytes, open cost is considered as scanning 4194304 bytes.
22/07/18 19:58:27 INFO SparkContext: Starting job: json at DemoSparkSQL.scala:10
22/07/18 19:58:27 INFO DAGScheduler: Got job 0 (json at DemoSparkSQL.scala:10) with 1 output partitions
22/07/18 19:58:27 INFO DAGScheduler: Final stage: ResultStage 0 (json at DemoSparkSQL.scala:10)
22/07/18 19:58:27 INFO DAGScheduler: Parents of final stage: List()
22/07/18 19:58:27 INFO DAGScheduler: Missing parents: List()
22/07/18 19:58:27 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[3] at json at DemoSparkSQL.scala:10), which has no missing parents
22/07/18 19:58:27 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 14.2 KiB, free 898.1 MiB)
22/07/18 19:58:27 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 6.7 KiB, free 898.1 MiB)
22/07/18 19:58:27 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.15.19:57168 (size: 6.7 KiB, free: 898.5 MiB)
22/07/18 19:58:27 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1513
22/07/18 19:58:27 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[3] at json at DemoSparkSQL.scala:10) (first 15 tasks are for partitions Vector(0))
22/07/18 19:58:27 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks resource profile 0
22/07/18 19:58:27 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0) (192.168.15.19, executor driver, partition 0, PROCESS_LOCAL, 7881 bytes) taskResourceAssignments Map()
22/07/18 19:58:27 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
22/07/18 19:58:27 INFO FileScanRDD: Reading File path: file:///C:/Users/Administrator/IdeaProjects/baidu1/src/info.json, range: 0-191, partition values: [empty row]
22/07/18 19:58:28 INFO CodeGenerator: Code generated in 193.9552 ms
22/07/18 19:58:28 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 2167 bytes result sent to driver
22/07/18 19:58:28 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 553 ms on 192.168.15.19 (executor driver) (1/1)
22/07/18 19:58:28 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
22/07/18 19:58:28 INFO DAGScheduler: ResultStage 0 (json at DemoSparkSQL.scala:10) finished in 0.728 s
22/07/18 19:58:28 INFO DAGScheduler: Job 0 is finished. Cancelling potential speculative or zombie tasks for this job
22/07/18 19:58:28 INFO TaskSchedulerImpl: Killing all running tasks in stage 0: Stage finished
22/07/18 19:58:28 INFO DAGScheduler: Job 0 finished: json at DemoSparkSQL.scala:10, took 0.766775 s
22/07/18 19:58:28 INFO FileSourceStrategy: Pushed Filters: IsNotNull(age),GreaterThanOrEqual(age,20)
22/07/18 19:58:28 INFO FileSourceStrategy: Post-Scan Filters: isnotnull(age#8L),(age#8L >= 20)
22/07/18 19:58:28 INFO FileSourceStrategy: Output Data Schema: struct<age: bigint, name: string>
22/07/18 19:58:28 INFO CodeGenerator: Code generated in 19.7363 ms
22/07/18 19:58:28 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 348.5 KiB, free 897.8 MiB)
22/07/18 19:58:28 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 33.7 KiB, free 897.7 MiB)
22/07/18 19:58:28 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 192.168.15.19:57168 (size: 33.7 KiB, free: 898.4 MiB)
22/07/18 19:58:28 INFO SparkContext: Created broadcast 2 from show at DemoSparkSQL.scala:14
22/07/18 19:58:28 INFO FileSourceScanExec: Planning scan with bin packing, max size: 4194304 bytes, open cost is considered as scanning 4194304 bytes.
22/07/18 19:58:28 INFO SparkContext: Starting job: show at DemoSparkSQL.scala:14
22/07/18 19:58:28 INFO DAGScheduler: Got job 1 (show at DemoSparkSQL.scala:14) with 1 output partitions
22/07/18 19:58:28 INFO DAGScheduler: Final stage: ResultStage 1 (show at DemoSparkSQL.scala:14)
22/07/18 19:58:28 INFO DAGScheduler: Parents of final stage: List()
22/07/18 19:58:28 INFO DAGScheduler: Missing parents: List()
22/07/18 19:58:28 INFO DAGScheduler: Submitting ResultStage 1 (MapPartitionsRDD[7] at show at DemoSparkSQL.scala:14), which has no missing parents
22/07/18 19:58:28 INFO MemoryStore: Block broadcast_3 stored as values in memory (estimated size 13.8 KiB, free 897.7 MiB)
22/07/18 19:58:28 INFO MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated size 6.9 KiB, free 897.7 MiB)
22/07/18 19:58:28 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on 192.168.15.19:57168 (size: 6.9 KiB, free: 898.4 MiB)
22/07/18 19:58:28 INFO SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:1513
22/07/18 19:58:28 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (MapPartitionsRDD[7] at show at DemoSparkSQL.scala:14) (first 15 tasks are for partitions Vector(0))
22/07/18 19:58:28 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks resource profile 0
22/07/18 19:58:28 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1) (192.168.15.19, executor driver, partition 0, PROCESS_LOCAL, 7881 bytes) taskResourceAssignments Map()
22/07/18 19:58:28 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
22/07/18 19:58:28 INFO FileScanRDD: Reading File path: file:///C:/Users/Administrator/IdeaProjects/baidu1/src/info.json, range: 0-191, partition values: [empty row]
22/07/18 19:58:28 INFO CodeGenerator: Code generated in 13.8558 ms
22/07/18 19:58:28 INFO CodeGenerator: Code generated in 6.469 ms
22/07/18 19:58:28 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1755 bytes result sent to driver
22/07/18 19:58:28 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 128 ms on 192.168.15.19 (executor driver) (1/1)
22/07/18 19:58:28 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool
22/07/18 19:58:28 INFO DAGScheduler: ResultStage 1 (show at DemoSparkSQL.scala:14) finished in 0.147 s
22/07/18 19:58:28 INFO DAGScheduler: Job 1 is finished. Cancelling potential speculative or zombie tasks for this job
22/07/18 19:58:28 INFO TaskSchedulerImpl: Killing all running tasks in stage 1: Stage finished
22/07/18 19:58:28 INFO DAGScheduler: Job 1 finished: show at DemoSparkSQL.scala:14, took 0.152033 s
22/07/18 19:58:28 INFO CodeGenerator: Code generated in 13.3474 ms
+---+------------+
|age| name|
+---+------------+
| 20| 静怡的梦莹|
| 21|潇洒的龙姑娘|
| 21| 优雅的秋兰|
+---+------------+

22/07/18 19:58:28 INFO SparkUI: Stopped Spark web UI at http://192.168.15.19:4040
22/07/18 19:58:28 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
22/07/18 19:58:28 INFO MemoryStore: MemoryStore cleared
22/07/18 19:58:28 INFO BlockManager: BlockManager stopped
22/07/18 19:58:28 INFO BlockManagerMaster: BlockManagerMaster stopped
22/07/18 19:58:28 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
22/07/18 19:58:28 INFO SparkContext: Successfully stopped SparkContext
22/07/18 19:58:28 INFO ShutdownHookManager: Shutdown hook called
22/07/18 19:58:28 INFO ShutdownHookManager: Deleting directory C:\Users\Administrator\AppData\Local\Temp\spark-04b6bffe-345b-4fc2-aaa2-a02c88e0dea4

Process finished with exit code 0

5、Demo2

package com.item.action

import org.apache.spark.sql.SparkSession

object Demo2 {
  def main(args: Array[String]): Unit = {
    //使用常量接受
    val spark2 = SparkSession.builder().appName("班长").master("local[*]")
      .getOrCreate()
    import spark2.implicits._
    //查询文件信息
    var df = spark2.read.json("info.json")
    //展示一下获取的数据
    df.show()
    df.filter($"age" > 20).show()
    df.filter($"age" > 20 && $"age" <= 22).show()
    df.filter(line => {
      if (line.toString().contains("雅")) {
        true
      } else {
        false
      }
    }).show()
    //sql
    //创建一个表
    df.createOrReplaceTempView("superGirl")
    //基础查询
    spark2.sql("select name,age from superGirl").show()
    //筛选
    spark2.sql("select name,age from superGirl where age>20 and age<22").show()
    spark2.sql("select name,age from superGirl where age between 20 and 22 order by age desc").show()
    //时间类型筛选
    spark2.sql(
      """
        |select * from superGirl where birthday>"2000-01-01 00:00:00"
        |""".stripMargin).show()
    spark2.sql(
      """
        |select * from superGirl where birthday between "2001-01-01 00:00:00" and "2002-12-01 00:00:00"
        |""".stripMargin).show()
    //分组、排序、聚合函数
    spark2.sql(
      """
        |select sex,count(*) from superGirl group by sex
        |""".stripMargin).show()
    spark2.sql(
      """
        |select * from superGirl where order by birthday asc
        |""".stripMargin).show()
    spark2.sql(
      """
        |select sum(age),count(*),round(avg(age),2),max(age),min(age) from superGirl
        |""".stripMargin).show()
    //关闭spark
    spark2.stop()
  }
}

+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 19|2001-05-06 12:00:00|娉婷的星望| 女|
| 20|1999-05-02 12:00:00|静怡的雷静| 女|
| 22|2000-01-06 12:00:00|潇洒的春梦| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
| 19|2002-05-09 12:00:00|玲珑的文静| 女|
| 18|2004-05-09 12:00:00|风雅的晓凤| 女|
+---+-------------------+----------+---+

+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 22|2000-01-06 12:00:00|潇洒的春梦| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
+---+-------------------+----------+---+

+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 22|2000-01-06 12:00:00|潇洒的春梦| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
+---+-------------------+----------+---+
+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
| 18|2004-05-09 12:00:00|风雅的晓凤| 女|
+---+-------------------+----------+---+

+----------+---+
| name|age|
+----------+---+
|娉婷的星望| 19|
|静怡的雷静| 20|
|潇洒的春梦| 22|
|优雅的蓉菲| 21|
|玲珑的文静| 19|
|风雅的晓凤| 18|
+----------+---+

+----------+---+
| name|age|
+----------+---+
|优雅的蓉菲| 21|
+----------+---+

+----------+---+
| name|age|
+----------+---+
|潇洒的春梦| 22|
|优雅的蓉菲| 21|
|静怡的雷静| 20|
+----------+---+
+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 19|2001-05-06 12:00:00|娉婷的星望| 女|
| 22|2000-01-06 12:00:00|潇洒的春梦| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
| 19|2002-05-09 12:00:00|玲珑的文静| 女|
| 18|2004-05-09 12:00:00|风雅的晓凤| 女|
+---+-------------------+----------+---+
+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 19|2001-05-06 12:00:00|娉婷的星望| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
| 19|2002-05-09 12:00:00|玲珑的文静| 女|
+---+-------------------+----------+---+
+---+--------+
|sex|count(1)|
+---+--------+
| 女| 6|
+---+--------+
+---+-------------------+----------+---+
|age| birthday| name|sex|
+---+-------------------+----------+---+
| 20|1999-05-02 12:00:00|静怡的雷静| 女|
| 22|2000-01-06 12:00:00|潇洒的春梦| 女|
| 19|2001-05-06 12:00:00|娉婷的星望| 女|
| 21|2001-06-06 12:00:00|优雅的蓉菲| 女|
| 19|2002-05-09 12:00:00|玲珑的文静| 女|
| 18|2004-05-09 12:00:00|风雅的晓凤| 女|
+---+-------------------+----------+---+
+--------+--------+------------------+--------+--------+
|sum(age)|count(1)|round(avg(age), 2)|max(age)|min(age)|
+--------+--------+------------------+--------+--------+
| 119| 6| 19.83| 22| 18|
+--------+--------+------------------+--------+--------+

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Spark高效数据分析03、Spack SQL

Spark高效数据分析03、Spack SQL

📋前言📋

环境需求

1、修改pom.xml

2、创建测试文件【info.json】，这里不是标准的json，面向行编写的【json】文件

3、SparkSession

4、Demo1

5、Demo2

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Spark高效数据分析03、Spack SQL

Spark高效数据分析03、Spack SQL

📋前言📋

环境需求

1、修改pom.xml

2、创建测试文件【info.json】，这里不是标准的json，面向行编写的【json】文件

3、SparkSession

4、Demo1

5、Demo2

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