hive on spark hql 插入数据报错 Failed to create Spark client for Spark session Error code 30041

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文章目录

一、遇到问题

离线数仓 hive on spark 模式，hive 客户端 sql 插入数据报错
Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create Spark client for Spark session 50cec71c-2636-4d99-8de2-a580ae3f1c58)'
FAILED: Execution Error, return code 30041 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Failed to create Spark client for Spark session 50cec71c-2636-4d99-8de2-a580ae3f1c58

以下是报错详情：

[hadoop@hadoop102 ~]$ hive
which: no hbase in (/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/datafs/module/jdk1.8.0_212/bin:/datafs/module/hadoop-3.1.3/bin:/datafs/module/hadoop-3.1.3/sbin:/datafs/module/zookeeper-3.5.7/bin:/datafs/module/kafka/bin:/datafs/module/flume/bin:/datafs/module/mysql-5.7.35/bin:/datafs/module/hive/bin:/datafs/module/spark/bin:/home/hadoop/.local/bin:/home/hadoop/bin)
Hive Session ID = 7db87c21-d9fb-4e76-a868-770691199377

Logging initialized using configuration in jar:file:/datafs/module/hive/lib/hive-common-3.1.2.jar!/hive-log4j2.properties Async: true
Hive Session ID = 24cd3001-0726-482f-9294-c901f49ace29
hive (default)> show databases;
OK
database_name
default
Time taken: 1.582 seconds, Fetched: 1 row(s)
hive (default)> show tables;
OK
tab_name
student
Time taken: 0.118 seconds, Fetched: 1 row(s)
hive (default)> select * from student;
OK
student.id      student.name
Time taken: 4.1 seconds
hive (default)> insert into table student values(1,'abc');
Query ID = hadoop_20220728195619_ded278b4-0ffa-41f2-9f2f-49313ea3d752
Total jobs = 1
Launching Job 1 out of 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create Spark client for Spark session 50cec71c-2636-4d99-8de2-a580ae3f1c58)'
FAILED: Execution Error, return code 30041 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Failed to create Spark client for Spark session 50cec71c-2636-4d99-8de2-a580ae3f1c58
hive (default)> [hadoop@hadoop102 ~]$

二、排查过程：

0、确认 hive、spark 版本

hive3.1.2：apache-hive-3.1.2-bin.tar.gz （重新编译之后的）

spark3.0.0：
+spark-3.0.0-bin-hadoop3.2.tgz
+spark-3.0.0-bin-without-hadoop.tgz

兼容性说明
注意：官网下载的 Hive 3.1.2 和 Spark 3.0.0 默认是不兼容的。因为 Hive3.1.2 支持的Spark版本是2.4.5，所以需要我们重新编译Hive3.1.2版本。
编译步骤：
官网下载Hive3.1.2源码，修改pom文件中引用的Spark版本为3.0.0，如果编译通过，直接打包获取jar包。如果报错，就根据提示，修改相关方法，直到不报错，打包获取jar包。

1、确认 SPARK_HOME 环境变量

[hadoop@hadoop102 software]$ sudo vim /etc/profile.d/my_env.sh
# 添加如下内容
# SPARK_HOME
export SPARK_HOME=/opt/module/spark
export PATH=$PATH:$SPARK_HOME/bin

source 使其生效

[hadoop@hadoop102 software]$ source /etc/profile.d/my_env.sh

2、hive 创建的 spark 配置文件

在hive中创建spark配置文件

[atguigu@hadoop102 software]$ vim /opt/module/hive/conf/spark-defaults.conf
# 添加如下内容（在执行任务时，会根据如下参数执行）
spark.master                               yarn
spark.eventLog.enabled                   true
spark.eventLog.dir                        hdfs://hadoop102:8020/spark-history
spark.executor.memory                    1g
spark.driver.memory					   1g

3、确认是否创建 hdfs 存储历史日志路径

确认存储历史日志路径是否创建

[hadoop@hadoop102 conf]$ hdfs dfs -ls /
Found 4 items
drwxr-xr-x   - hadoop supergroup          0 2022-07-28 20:31 /spark-history
drwxr-xr-x   - hadoop supergroup          0 2022-03-15 16:42 /test
drwxrwx---   - hadoop supergroup          0 2022-03-16 09:14 /tmp
drwxrwxrwx   - hadoop supergroup          0 2022-07-28 18:38 /user

若不存在，则需要在HDFS创建如下路径

[hadoop@hadoop102 software]$ hadoop fs -mkdir /spark-history

4、确认 是否上传 Spark 纯净版 jar 包

说明1：由于Spark3.0.0非纯净版默认支持的是hive2.3.7版本，直接使用会和安装的Hive3.1.2出现兼容性问题。所以采用Spark纯净版jar包，不包含hadoop和hive相关依赖，避免冲突。

说明2：Hive任务最终由Spark来执行，Spark任务资源分配由Yarn来调度，该任务有可能被分配到集群的任何一个节点。所以需要将Spark的依赖上传到HDFS集群路径，这样集群中任何一个节点都能获取到。

[hadoop@hadoop102 software]$ tar -zxvf /opt/software/spark-3.0.0-bin-without-hadoop.tgz

上传Spark纯净版jar包到HDFS

[hadoop@hadoop102 software]$ hadoop fs -mkdir /spark-jars

[hadoop@hadoop102 software]$ hadoop fs -put spark-3.0.0-bin-without-hadoop/jars/* /spark-jars

5、确认 hive-site.xml 配置文件

[hadoop@hadoop102 ~]$ vim /opt/module/hive/conf/hive-site.xml

添加如下内容

<!--Spark依赖位置（注意：端口号8020必须和namenode的端口号一致）-->
<property>
    <name>spark.yarn.jars</name>
    <value>hdfs://hadoop102:8020/spark-jars/*</value>
</property>
  
<!--Hive执行引擎-->
<property>
    <name>hive.execution.engine</name>
    <value>spark</value>
</property>

三、解决问题

在 hive/conf/hive-site.xml中追加：
（这里延长了 hive 和 spark 连接的时间，可以有效避免超时报错）

<!--Hive和spark连接超时时间-->
<property>
    <name>hive.spark.client.connect.timeout</name>
    <value>100000ms</value>
</property>

这时，重新打开 hive 客户端，插入数据正常无报错

[hadoop@hadoop102 conf]$ hive
which: no hbase in (/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/datafs/module/jdk1.8.0_212/bin:/datafs/module/hadoop-3.1.3/bin:/datafs/module/hadoop-3.1.3/sbin:/datafs/module/zookeeper-3.5.7/bin:/datafs/module/kafka/bin:/datafs/module/flume/bin:/datafs/module/mysql-5.7.35/bin:/datafs/module/hive/bin:/datafs/module/spark/bin:/home/hadoop/.local/bin:/home/hadoop/bin)
Hive Session ID = b7564f00-0c04-45fd-9984-4ecd6e6149c2

Logging initialized using configuration in jar:file:/datafs/module/hive/lib/hive-common-3.1.2.jar!/hive-log4j2.properties Async: true
Hive Session ID = e4af620a-8b6a-422e-b921-5d6c58b81293
hive (default)>

插入第一条数据，需要初始化 spark session 所以慢

hive (default)> insert into table student values(1,'abc');
Query ID = hadoop_20220728201636_11b37058-89dc-4050-a4bf-1dcf404bd579
Total jobs = 1
Launching Job 1 out of 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Running with YARN Application = application_1659005322171_0009
Kill Command = /datafs/module/hadoop-3.1.3/bin/yarn application -kill application_1659005322171_0009
Hive on Spark Session Web UI URL: http://hadoop104:38030

Query Hive on Spark job[0] stages: [0, 1]
Spark job[0] status = RUNNING
--------------------------------------------------------------------------------------
          STAGES   ATTEMPT        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED
--------------------------------------------------------------------------------------
Stage-0 ........         0      FINISHED      1          1        0        0       0
Stage-1 ........         0      FINISHED      1          1        0        0       0
--------------------------------------------------------------------------------------
STAGES: 02/02    [==========================>>] 100%  ELAPSED TIME: 40.06 s
--------------------------------------------------------------------------------------
Spark job[0] finished successfully in 40.06 second(s)
WARNING: Spark Job[0] Spent 16% (3986 ms / 25006 ms) of task time in GC
Loading data to table default.student
OK
col1    col2
Time taken: 127.46 seconds
hive (default)>

下面再插入数据就快了

hive (default)> insert into table student values(2,'ddd');
Query ID = hadoop_20220728202000_1093388b-3ec6-45e5-a9f1-1b07c64f2583
Total jobs = 1
Launching Job 1 out of 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Running with YARN Application = application_1659005322171_0009
Kill Command = /datafs/module/hadoop-3.1.3/bin/yarn application -kill application_1659005322171_0009
Hive on Spark Session Web UI URL: http://hadoop104:38030

Query Hive on Spark job[1] stages: [2, 3]
Spark job[1] status = RUNNING
--------------------------------------------------------------------------------------
          STAGES   ATTEMPT        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED
--------------------------------------------------------------------------------------
Stage-2 ........         0      FINISHED      1          1        0        0       0
Stage-3 ........         0      FINISHED      1          1        0        0       0
--------------------------------------------------------------------------------------
STAGES: 02/02    [==========================>>] 100%  ELAPSED TIME: 2.12 s
--------------------------------------------------------------------------------------
Spark job[1] finished successfully in 3.20 second(s)
Loading data to table default.student
OK
col1    col2
Time taken: 6.0 seconds
hive (default)>

查询数据

hive (default)> select * from student;
OK
student.id      student.name
1       abc
2       ddd
Time taken: 0.445 seconds, Fetched: 2 row(s)
hive (default)> [hadoop@hadoop102 conf]$

四、后记

遇到问题，不放弃
网上搜索了很多解决方案，不靠谱的很多
靠谱的是这个大佬在 https://b23.tv/hzvzdJc 评论区写的

尝试到第三种思路，瞬间解决

第一条数据插入成功的那一刻，是久违的成就感，开心

分享这篇 blog，一是记录解决问题的过程，二是帮助萌新小白

我们下期见，拜拜！

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