大数据最全大数据进阶之路——Spark SQL基本配置_spark，2024年最新一个APP从启动到主页面显示经历了哪些过程

于 2024-05-15 15:58:49 发布
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本地IDE

A master URL must be set in your configuration

点击edit configuration，在左侧点击该项目。在右侧VM options中输入“-Dspark.master=local”，指示本程序本地单线程运行，再次运行即可。

package org.example

import org.apache.spark.sql.SQLContext
import org.apache.spark.{SparkConf, SparkContext}

object SQLContextAPP {
  def main(args: Array[String]): Unit = {
    //1创建相应的Spark
    val sparkConf = new SparkConf()
    sparkConf.setAppName("SQLContextAPP")
    val sc = new SparkContext(sparkConf)
    val sqlContext = new SQLContext(sc)

    //2数据处理
    val people = sqlContext.read.format("json").load("people.json")
    people.printSchema()
    people.show()

    //3关闭资源
    sc.stop()


  }

}




root
 |-- age: long (nullable = true)
 |-- name: string (nullable = true)

.........................


| age|   name|
+----+-------+
|null|Michael|
|  30|   Andy|
|  19| Justin|
+----+-------+

配置maven环境变量cmd控制台提示：mvn不是内部或外部命令，也不是可运行的程序或批处理文件

首先maven环境变量：


变量名：MAVEN_HOME

变量值：E:\apache-maven-3.2.3

变量名：Path

变量值：;%MAVEN_HOME%\bin

然后到项目的目录下直接执行

C:\Users\jacksun\IdeaProjects\SqarkSQL\ mvn clean package -DskipTests

在集群上测试

spark-submit \
--name SQLContextApp \
--class org.example.SQLContextApp \
--master local[2] \
/home/hadoop/lib/sql-1.0.jar \
/home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/examples/src/main/resources/people.json
HiveContextAPP

注意：
1）To use a HiveContext, you do not need to have an existing Hive setup
2）hive-site.xml

package org.example

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.hive.HiveContext

object HiveContextAPP {
  def main(args: Array[String]): Unit = {
    //1创建相应的Spark
    val path =args(0)
    val sparkConf = new SparkConf()

    //测试和生产中AppName和Master是通过脚本执行的
    //sparkConf.setAppName("HiveContextAPP").setMaster("local[2]")



    val sc = new SparkContext(sparkConf)
    val hiveContext = new HiveContext(sc)

    //2数据处理
    hiveContext.table("emp").show

    //3关闭资源
    sc.stop()


  }
}




spark-submit \
--name HiveContextApp \
--class org.example.HiveContextApp \
--master local[2] \
/home/hadoop/lib/sql-1.0.jar \
--jars /home/hadoop/software/mysql-connector-java-5.1.27-bin.jar
SparkSessinon
package org.example

import org.apache.spark.sql.SparkSession

object SparkSessionApp {
  def main(args: Array[String]) {

    val spark = SparkSession.builder().appName("SparkSessionApp")
      .master("local[2]").getOrCreate()

    val people = spark.read.json("people.json")
    people.show()

    spark.stop()
  }
}
Spark Shell
  • 启动hive
[hadoop@hadoop001 bin]$ pwd
/home/hadoop/app/hive-1.1.0-cdh5.7.0/bin
[hadoop@hadoop001 bin]$ hive
ls: cannot access /home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/lib/spark-assembly-\*.jar: No such file or directory
which: no hbase in (/home/hadoop/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/bin:/home/hadoop/app/scala-2.11.8/bin:/home/hadoop/app/hive-1.1.0-cdh5.7.0/bin:/home/hadoop/app/hadoop-2.6.0-cdh5.7.0/bin:/home/hadoop/app/apache-maven-3.3.9/bin:/home/hadoop/app/jdk1.7.0_51/bin:/usr/local/bin:/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/sbin)

Logging initialized using configuration in jar:file:/home/hadoop/app/hive-1.1.0-cdh5.7.0/lib/hive-common-1.1.0-cdh5.7.0.jar!/hive-log4j.properties
WARNING: Hive CLI is deprecated and migration to Beeline is recommended.
hive>
  • 拷贝
    [hadoop@hadoop001 conf]$ cp hive-site.xml ~/app/spark-2.1.0-bin-2.6.0-cdh5.7.0/conf/
  • 启动Spark
    spark-shell --master local[2] --jars /home/hadoop/software/mysql-connector-java-5.1.27-bin.jar
scala> spark.sql("show tables").show
+--------+------------+-----------+
|database|   tableName|isTemporary|
+--------+------------+-----------+
| default|        dept|      false|
| default|         emp|      false|
| default|hive_table_1|      false|
| default|hive_table_2|      false|
| default|           t|      false|
+--------+------------+-----------+


hive> show tables;
OK
dept
emp
hive_wordcount




scala> spark.sql("select \* from emp e join dept d on e.deptno=d.deptno").show
+-----+------+---------+----+----------+------+------+------+------+----------+--------+
|empno| ename|      job| mgr|  hiredate|   sal|  comm|deptno|deptno|     dname|     loc|
+-----+------+---------+----+----------+------+------+------+------+----------+--------+
| 7369| SMITH|    CLERK|7902|1980-12-17| 800.0|  null|    20|    20|  RESEARCH|  DALLAS|
| 7499| ALLEN| SALESMAN|7698| 1981-2-20|1600.0| 300.0|    30|    30|     SALES| CHICAGO|
| 7521|  WARD| SALESMAN|7698| 1981-2-22|1250.0| 500.0|    30|    30|     SALES| CHICAGO|
| 7566| JONES|  MANAGER|7839|  1981-4-2|2975.0|  null|    20|    20|  RESEARCH|  DALLAS|
| 7654|MARTIN| SALESMAN|7698| 1981-9-28|1250.0|1400.0|    30|    30|     SALES| CHICAGO|
| 7698| BLAKE|  MANAGER|7839|  1981-5-1|2850.0|  null|    30|    30|     SALES| CHICAGO|
| 7782| CLARK|  MANAGER|7839|  1981-6-9|2450.0|  null|    10|    10|ACCOUNTING|NEW YORK|
| 7788| SCOTT|  ANALYST|7566| 1987-4-19|3000.0|  null|    20|    20|  RESEARCH|  DALLAS|
| 7839|  KING|PRESIDENT|null|1981-11-17|5000.0|  null|    10|    10|ACCOUNTING|NEW YORK|
| 7844|TURNER| SALESMAN|7698|  1981-9-8|1500.0|   0.0|    30|    30|     SALES| CHICAGO|
| 7876| ADAMS|    CLERK|7788| 1987-5-23|1100.0|  null|    20|    20|  RESEARCH|  DALLAS|
| 7900| JAMES|    CLERK|7698| 1981-12-3| 950.0|  null|    30|    30|     SALES| CHICAGO|
| 7902|  FORD|  ANALYST|7566| 1981-12-3|3000.0|  null|    20|    20|  RESEARCH|  DALLAS|
| 7934|MILLER|    CLERK|7782| 1982-1-23|1300.0|  null|    10|    10|ACCOUNTING|NEW YORK|
+-----+------+---------+----+----------+------+------+------+------+----------+--------+

hive> select \* from emp e join dept d on e.deptno=d.deptno
    > ;
Query ID = hadoop_20201020054545_f7fbda3e-439e-409e-b2ce-3c553d969ed4
Total jobs = 1
20/10/20 05:48:46 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Execution log at: /tmp/hadoop/hadoop_20201020054545_f7fbda3e-439e-409e-b2ce-3c553d969ed4.log
2020-10-20 05:48:49	Starting to launch local task to process map join;	maximum memory = 477102080
2020-10-20 05:48:51	Dump the side-table for tag: 1 with group count: 4 into file: file:/tmp/hadoop/5c8577b3-c00d-4ece-9899-c0e3de66f2f2/hive_2020-10-20_05-48-27_437_556791932773953494-1/-local-10003/HashTable-Stage-3/MapJoin-mapfile01--.hashtable
2020-10-20 05:48:51	Uploaded 1 File to: file:/tmp/hadoop/5c8577b3-c00d-4ece-9899-c0e3de66f2f2/hive_2020-10-20_05-48-27_437_556791932773953494-1/-local-10003/HashTable-Stage-3/MapJoin-mapfile01--.hashtable (404 bytes)
2020-10-20 05:48:51	End of local task; Time Taken: 2.691 sec.
Execution completed successfully
MapredLocal task succeeded
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1602849227137_0002, Tracking URL = http://hadoop001:8088/proxy/application_1602849227137_0002/
Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.7.0/bin/hadoop job  -kill job_1602849227137_0002
Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 0
2020-10-20 05:49:13,663 Stage-3 map = 0%,  reduce = 0%
2020-10-20 05:49:36,950 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 13.08 sec
MapReduce Total cumulative CPU time: 13 seconds 80 msec
Ended Job = job_1602849227137_0002
MapReduce Jobs Launched: 
Stage-Stage-3: Map: 1   Cumulative CPU: 13.08 sec   HDFS Read: 7639 HDFS Write: 927 SUCCESS
Total MapReduce CPU Time Spent: 13 seconds 80 msec
OK
7369	SMITH	CLERK	7902	1980-12-17	800.0	NULL	20	20	RESEARCH	DALLAS
7499	ALLEN	SALESMAN	7698	1981-2-20	1600.0	300.0	30	30	SALES	CHICAGO
7521	WARD	SALESMAN	7698	1981-2-22	1250.0	500.0	30	30	SALES	CHICAGO
7566	JONES	MANAGER	7839	1981-4-2	2975.0	NULL	20	20	RESEARCH	DALLAS
7654	MARTIN	SALESMAN	7698	1981-9-28	1250.0	1400.0	30	30	SALES	CHICAGO
7698	BLAKE	MANAGER	7839	1981-5-1	2850.0	NULL	30	30	SALES	CHICAGO
7782	CLARK	MANAGER	7839	1981-6-9	2450.0	NULL	10	10	ACCOUNTING	NEW YORK
7788	SCOTT	ANALYST	7566	1987-4-19	3000.0	NULL	20	20	RESEARCH	DALLAS
7839	KING	PRESIDENT	NULL	1981-11-17	5000.0	NULL	10	10	ACCOUNTINGNEW YORK
7844	TURNER	SALESMAN	7698	1981-9-8	1500.0	0.0	30	30	SALES	CHICAGO
7876	ADAMS	CLERK	7788	1987-5-23	1100.0	NULL	20	20	RESEARCH	DALLAS
7900	JAMES	CLERK	7698	1981-12-3	950.0	NULL	30	30	SALES	CHICAGO
7902	FORD	ANALYST	7566	1981-12-3	3000.0	NULL	20	20	RESEARCH	DALLAS
7934	MILLER	CLERK	7782	1982-1-23	1300.0	NULL	10	10	ACCOUNTING	NEW YORK
Time taken: 71.998 seconds, Fetched: 14 row(s)
hive>

SPARK SQL 基本秒出结果,hive比较耗时

  • hive-site.xml
    删除警告
<property>
  <name>hive.metastore.schema.verification</name>
  <value>false</value>
</property>
Spark Sql
20/10/20 06:20:09 INFO DAGScheduler: Job 1 finished: processCmd at CliDriver.java:376, took 0.261151 s
7369	SMITH	CLERK	7902	1980-12-17	800.0	NULL	20	20	RESEARCH	DALLAS
7499	ALLEN	SALESMAN	7698	1981-2-20	1600.0	300.0	30	30	SALES	CHICAGO
7521	WARD	SALESMAN	7698	1981-2-22	1250.0	500.0	30	30	SALES	CHICAGO
7566	JONES	MANAGER	7839	1981-4-2	2975.0	NULL	20	20	RESEARCH	DALLAS
7654	MARTIN	SALESMAN	7698	1981-9-28	1250.0	1400.0	30	30	SALES	CHICAGO
7698	BLAKE	MANAGER	7839	1981-5-1	2850.0	NULL	30	30	SALES	CHICAGO
7782	CLARK	MANAGER	7839	1981-6-9	2450.0	NULL	10	10	ACCOUNTING	NEW YORK
7788	SCOTT	ANALYST	7566	1987-4-19	3000.0	NULL	20	20	RESEARCH	DALLAS
7839	KING	PRESIDENT	NULL	1981-11-17	5000.0	NULL	10	10	ACCOUNTINGNEW YORK
7844	TURNER	SALESMAN	7698	1981-9-8	1500.0	0.0	30	30	SALES	CHICAGO
7876	ADAMS	CLERK	7788	1987-5-23	1100.0	NULL	20	20	RESEARCH	DALLAS
7900	JAMES	CLERK	7698	1981-12-3	950.0	NULL	30	30	SALES	CHICAGO
7902	FORD	ANALYST	7566	1981-12-3	3000.0	NULL	20	20	RESEARCH	DALLAS
7934	MILLER	CLERK	7782	1982-1-23	1300.0	NULL	10	10	ACCOUNTING	NEW YORK
Time taken: 13.625 seconds, Fetched 14 row(s)
20/10/20 06:20:09 INFO CliDriver: Time taken: 13.625 seconds, Fetched 14 row(s)

explain extended select a.key*(2+3), b.value from t a join t b on a.key = b.key and a.key > 3;

== Parsed Logical Plan ==
'Project [unresolvedalias(('a.key \* (2 + 3)), None), 'b.value]
+- 'Join Inner, (('a.key = 'b.key) && ('a.key > 3))
   :- 'UnresolvedRelation `t`, a
   +- 'UnresolvedRelation `t`, b

== Analyzed Logical Plan ==
(CAST(key AS DOUBLE) \* CAST((2 + 3) AS DOUBLE)): double, value: string
Project [(cast(key#321 as double) \* cast((2 + 3) as double)) AS (CAST(key AS DOUBLE) \* CAST((2 + 3) AS DOUBLE))#325, value#324]
+- Join Inner, ((key#321 = key#323) && (cast(key#321 as double) > cast(3 as double)))
   :- SubqueryAlias a
   :  +- MetastoreRelation default, t
   +- SubqueryAlias b
      +- MetastoreRelation default, t

== Optimized Logical Plan ==
Project [(cast(key#321 as double) \* 5.0) AS (CAST(key AS DOUBLE) \* CAST((2 + 3) AS DOUBLE))#325, value#324]
+- Join Inner, (key#321 = key#323)
   :- Project [key#321]
   :  +- Filter (isnotnull(key#321) && (cast(key#321 as double) > 3.0))
   :     +- MetastoreRelation default, t
   +- Filter (isnotnull(key#323) && (cast(key#323 as double) > 3.0))
      +- MetastoreRelation default, t

== Physical Plan ==
\*Project [(cast(key#321 as double) \* 5.0) AS (CAST(key AS DOUBLE) \* CAST((2 + 3) AS DOUBLE))#325, value#324]
+- \*SortMergeJoin [key#321], [key#323], Inner
   :- \*Sort [key#321 ASC NULLS FIRST], false, 0
   :  +- Exchange hashpartitioning(key#321, 200)
   :     +- \*Filter (isnotnull(key#321) && (cast(key#321 as double) > 3.0))
   :        +- HiveTableScan [key#321], MetastoreRelation default, t
   +- \*Sort [key#323 ASC NULLS FIRST], false, 0
      +- Exchange hashpartitioning(key#323, 200)
         +- \*Filter (isnotnull(key#323) && (cast(key#323 as double) > 3.0))
            +- HiveTableScan [key#323, value#324], MetastoreRelation default, t
thriftserver/beeline的使用

spark下的sbin

  1. 启动thriftserver:
    ./start-thriftserver.sh --master local[2] --jars /home/hadoop/software/mysql-connector-java-5.1.27-bin.jar

默认端口是10000 ，可以修改

./start-thriftserver.sh  \
--master local[2] \
--jars ~/software/mysql-connector-java-5.1.27-bin.jar  \
--hiveconf hive.server2.thrift.port=14000

2）启动beeline
beeline -u jdbc:hive2://localhost:10000 -n hadoop

beeline -u jdbc:hive2://localhost:14000 -n hadoop

thriftserver和普通的spark-shell/spark-sql有什么区别？

1）spark-shell、spark-sql都是一个spark application；
2）thriftserver

  • 不管你启动多少个客户端(beeline/code)，永远都是一个spark application
  • 解决了一个数据共享的问题，多个客户端可以共享数据；
jdbc
注意事项：在使用jdbc开发时，一定要先启动thriftserver
Exception in thread "main" java.sql.SQLException: 
Could not open client transport with JDBC Uri: jdbc:hive2://hadoop001:14000: 
java.net.ConnectException: Connection refused




<dependency>
      <groupId>org.spark-project.hive</groupId>
      <artifactId>hive-jdbc</artifactId>
      <version>1.2.1.spark2</version>
      <!--
      <scope>provided</scope>
      -->
    </dependency>



package org.example
import java.sql.DriverManager
object JDBCApp {



![img](https://img-blog.csdnimg.cn/img_convert/8b90172ac8e3ae71e78abf3f7d2b0da2.png)
![img](https://img-blog.csdnimg.cn/img_convert/f72c170b06c71fef6b3830ee867ba67d.png)

**网上学习资料一大堆，但如果学到的知识不成体系，遇到问题时只是浅尝辄止，不再深入研究，那么很难做到真正的技术提升。**

**[需要这份系统化资料的朋友，可以戳这里获取](https://bbs.youkuaiyun.com/topics/618545628)**


**一个人可以走的很快，但一群人才能走的更远！不论你是正从事IT行业的老鸟或是对IT行业感兴趣的新人，都欢迎加入我们的的圈子（技术交流、学习资源、职场吐槽、大厂内推、面试辅导），让我们一起学习成长！**

on>1.2.1.spark2</version>
      <!--
      <scope>provided</scope>
      -->
    </dependency>



package org.example
import java.sql.DriverManager
object JDBCApp {



[外链图片转存中...(img-Wrxoaqfp-1715759907695)]
[外链图片转存中...(img-V4hLYpbY-1715759907696)]

**网上学习资料一大堆，但如果学到的知识不成体系，遇到问题时只是浅尝辄止，不再深入研究，那么很难做到真正的技术提升。**

**[需要这份系统化资料的朋友，可以戳这里获取](https://bbs.youkuaiyun.com/topics/618545628)**


**一个人可以走的很快，但一群人才能走的更远！不论你是正从事IT行业的老鸟或是对IT行业感兴趣的新人，都欢迎加入我们的的圈子（技术交流、学习资源、职场吐槽、大厂内推、面试辅导），让我们一起学习成长！**
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