java-1.8.0-openjdk-1.8.0.181-7.b13.el7
hadoop-2.5.2
spark-2.3.3
hbase-1.3.1
hbase-2.1.0
zookeeper-3.5.5-bin
janusgraph-0.2.0-hadoop2-gremlin
mysql-5.7.27
hive-2.1.1
这两天我配置了mysql和hive,本文记录遇到的问题。
使用了arm架构下的mysql.tar.gz离线安装。
参考文章:ARM架构部署mysql-5.7.27
文章内容:
cd /usr/local
将部署包:mysql-5.7.27-aarch64.tar.gz 上传到 /usr/local 下
tar xvf mysql-5.7.27-aarch64.tar.gz
mv /usr/local/mysql-5.7.27-aarch64 /usr/local/mysql
mkdir -p /usr/local/mysql/logs
ln -sf /usr/local/mysql/my.cnf /etc/my.cnf
cp -rf /usr/local/mysql/extra/lib* /usr/lib64/
mv /usr/lib64/libstdc++.so.6 /usr/lib64/libstdc++.so.6.old
ln -s /usr/lib64/libstdc++.so.6.0.24 /usr/lib64/libstdc++.so.6
groupadd mysql
useradd -g mysql mysql
chown -R mysql:mysql /usr/local/mysql
cp -rf /usr/local/mysql/support-files/mysql.server /etc/init.d/mysqld
chmod +x /etc/init.d/mysqld
systemctl enable mysqld
vim /etc/profile
export MYSQL_HOME=/usr/local/mysql
export PATH=$PATH:$MYSQL_HOME/bin
source /etc/profile
mysqld --initialize-insecure --user=mysql --basedir=/usr/local/mysql --datadir=/usr/local/mysql/data
systemctl start mysqld
systemctl status mysqld
移动文件 mv /usr/local/mysql-5.7.27-aarch64 /usr/local/mysql
创建logs目录 mkdir -p /usr/local/mysql/logs
ln -sf a b 建立软连接,b指向a:ln -sf /usr/local/mysql/my.cnf /etc/my.cnf
cp是linux里的拷贝命令-r 是用于目录拷贝时的递归操作-f 是强制覆盖:cp -rf /usr/local/mysql/extra/lib* /usr/lib64/
创建mysql组:ln -s /usr/lib64/libstdc++.so.6.0.24 /usr/lib64/libstdc++.so.6
创建mysql用户添加到mysql组:groupadd mysql && useradd -g mysql mysql
将/usr/loca/mysql目录包含所有的子目录和文件,所有者改变为root,所属组改变为mysql:chown -R mysql:mysql /usr/local/mysql
设置开机启动:
cp -rf /usr/local/mysql/support-files/mysql.server /etc/init.d/mysqld
chmod +x /etc/init.d/mysqld
systemctl enable mysqld
添加环境变量:
vim /etc/profile
export MYSQL_HOME=/usr/local/mysql
export PATH=PATH:PATH:PATH:MYSQL_HOME/bin
source /etc/profile
初始化mysql:mysqld --initialize-insecure --user=mysql --basedir=/usr/local/mysql --datadir=/usr/local/mysql/data
开启mysql:systemctl start mysqld
查看状态:systemctl status mysqld
重点检查my.cnf文件,所有目录的创建,权限,初始化命令参数。
关于my.cnf的详细介绍参考:MySQL 配置文件 my.cnf / my.ini 逐行解析
原文内容:
MySQL 配置文件详解
文件位置: Windows、Linux、Mac 有细微区别,Windows 配置文件是 .ini,Mac/linux 是 .cnf
[Windows]
MySQL\MySQL Server 5.7\my.ini
[Linux / Mac]
/etc/my.cnf
/etc/mysql/my.cnf
当然我们也可以使用命令来查看 MySQL 默认配置文件位置
mysql --help|grep 'cnf'
[client]
客户端设置。当前为客户端默认参数
port = 3306
默认连接端口为 3306
socket = /tmp/mysql.sock
本地连接的 socket 套接字
default_character_set = utf8
设置字符集,通常使用 uft8 即可
[mysqld_safe]
mysqld_safe 是服务器端工具,用于启动 mysqld,也是 mysqld 的守护进程。当 mysql 被 kill 时,mysqld_safe 负责重启启动它。
open_files_limit = 8192
此为 MySQL 打开的文件描述符限制,它是 MySQL 中的一个全局变量且不可动态修改。它控制着 mysqld 进程能使用的最大文件描述符数量。默认最小值为 1024
需要注意的是这个变量的值并不一定是你在这里设置的值,mysqld 会在系统允许的情况下尽量取最大值。
当 open_files_limit 没有被配置时,比较 max_connections*5 和 ulimit -n 的值,取最大值
当 open_file_limit 被配置时,比较 open_files_limit 和 max_connections*5 的值,取最大值
user = mysql
用户名
log-error = error.log
错误 log 记录文件
[mysqld]
服务端基本配置
port = 3306
mysqld 服务端监听端口
socket = /tmp/mysql.sock
MySQL 客户端程序和服务器之间的本地通讯指定一个套接字文件
max_allowed_packet = 16M
允许最大接收数据包的大小,防止服务器发送过大的数据包。
当发出长查询或 mysqld 返回较大结果时,mysqld 才会分配内存,所以增大这个值风险不大,默认 16M,也可以根据需求改大,但太大会有溢出风险。取较小值是一种安全措施,避免偶然出现但大数据包导致内存溢出。
default_storage_engine = InnoDB
创建数据表时,默认使用的存储引擎。这个变量还可以通过 –default-table-type 进行设置
max_connections = 512
最大连接数,当前服务器允许多少并发连接。默认为 100,一般设置为小于 1000 即可。太高会导致内存占用过多,MySQL 服务器会卡死。作为参考,小型站设置 100 - 300
max_user_connections = 50
用户最大的连接数,默认值为 50 一般使用默认即可。
thread_cache_size = 64
线程缓存,用于缓存空闲的线程。这个数表示可重新使用保存在缓存中的线程数,当对方断开连接时,如果缓存还有空间,那么客户端的线程就会被放到缓存中,以便提高系统性能。我们可根据物理内存来对这个值进行设置,对应规则 1G 为 8;2G 为 16;3G 为 32;4G 为 64 等。
Query Cache
query_cache_type = 1
设置为 0 时,则禁用查询缓存(尽管仍分配query_cache_size个字节的缓冲区)。
设置为 1 时 ,除非指定SQL_NO_CACHE,否则所有SELECT查询都将被缓存。
设置为 2 时,则仅缓存带有SQL CACHE子句的查询。
请注意,如果在禁用查询缓存的情况下启动服务器,则无法在运行时启用服务器。
query_cache_size = 64M
缓存select语句和结果集大小的参数。
查询缓存会存储一个select查询的文本与被传送到客户端的相应结果。
如果之后接收到一个相同的查询,服务器会从查询缓存中检索结果,而不是再次分析和执行这个同样的查询。
如果你的环境中写操作很少,读操作频繁,那么打开query_cache_type=1,会对性能有明显提升。如果写操作频繁,则应该关闭它(query_cache_type=0)。
Session variables sort_buffer_size = 2M
MySQL 执行排序时,使用的缓存大小。增大这个缓存,提高 group by,order by 的执行速度。
tmp_table_size = 32M
HEAP 临时数据表的最大长度,超过这个长度的临时数据表 MySQL 可根据需求自动将基于内存的 HEAP 临时表改为基于硬盘的 MyISAM 表。我们可通过调整 tmp_table_size 的参数达到提高连接查询速度的效果。
read_buffer_size = 128k
MySQL 读入缓存的大小。如果对表对顺序请求比较频繁对话,可通过增加该变量值以提高性能。
read_rnd_buffer_size = 256k
用于表的随机读取,读取时每个线程分配的缓存区大小。默认为 256k ,一般在 128 - 256k之间。在做 order by 排序操作时,会用到 read_rnd_buffer_size 空间来暂做缓冲空间。
join_buffer_size = 128k
程序中经常会出现一些两表或多表 Join (联表查询)的操作。为了减少参与 Join 连表的读取次数以提高性能,需要用到 Join Buffer 来协助 Join 完成操作。当 Join Buffer 太小时,MySQL 不会将它写入磁盘文件。和 sort_buffer_size 一样,此参数的内存分配也是每个连接独享。
table_definition_cache = 400
限制不使用文件描述符存储在缓存中的表定义的数量。
table_open_cache = 400
限制为所有线程在内存中打开的表数量。
MySQL 错误日志设置
log_error = error.log log_warnings = 2
log_warnings 为0, 表示不记录告警信息。
log_warnings 为1, 表示告警信息写入错误日志。
log_warnings 大于1, 表示各类告警信息,例如有关网络故障的信息和重新连接信息写入错误日志。
慢查询记录
slow_query_log_file = slow.log slow_query_log = 0 log_queries_not_using_indexes = 1 long_query_time = 0.5 min_examined_row_limit = 100
slow_query_log :全局开启慢查询功能。
slow_query_log_file :指定慢查询日志存储文件的地址和文件名。
log_queries_not_using_indexes:无论是否超时,未被索引的记录也会记录下来。
long_query_time:慢查询阈值(秒),SQL 执行超过这个阈值将被记录在日志中。
min_examined_row_limit:慢查询仅记录扫描行数大于此参数的 SQL。
报错内容:
Job for mysqld.service failed because the control process exited with error code. See “systemctl status mysqld.service” and “journalctl -xe” for details.
解决思路:
mysqld.pid目录权限问题,请把我们组群mysql:mysql给到权限,这个组群是我们安装mysql时创建的。
参考文章:
[1]:关于Job for mysqld.service failed because the control process exited with error code报错解决办法
[2]:启动mysql报错Job for mysqld.service failed because the control process exited with error code.
报错内容:
ERROR Could not open file ‘***/log/mysql/error.log‘ for error logging: Permission denied
**错误原因:**日志文件夹的权限问题,请重点用chmod检查权限是否够组群用户使用。
参考文档:
[1]:centos系统中MySQL无法启动的问题
[2]:Docker中mysql启动错误Could not open file ‘/var/log/mysqld.log‘ for error logging: Permission denied
报错内容:
Starting MySQL... ERROR The server quit without updating PID file
参考文档:
启动mysql服务时一直提示ERROR The server quit without updating PID file
该文章分析了启动mysql的几个服务脚本源码,非常详细,介绍了用户权限对mysql初始化的影响以及pid文件在此的作用,包括mycnf的配置目录描述。再次重启时可以使用mysql.service或者mysqld_safe来启动mysql。
### 2.1.1 报错信息:org.apache.hadoop.yarn.exceptions.InvalidAuxServiceException: The auxService:mapreduce_shuffle does not exist
以下报错日志是我在我的个人集群中更改配置后复现的报错结果,其中运行了mapreduce官方案例的wordcount和pi:
[root@hadoop11 data]# hadoop jar /opt/installs/hadoop3.1.4/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.4.jar wordcount /wc.txt /out3
2023-10-09 15:42:20,213 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /tmp/hadoop-yarn/staging/root/.staging/job_1696837267350_0001
2023-10-09 15:42:20,536 INFO input.FileInputFormat: Total input files to process : 1
2023-10-09 15:42:20,684 INFO mapreduce.JobSubmitter: number of splits:1
2023-10-09 15:42:20,955 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1696837267350_0001
2023-10-09 15:42:20,959 INFO mapreduce.JobSubmitter: Executing with tokens: []
2023-10-09 15:42:21,212 INFO conf.Configuration: resource-types.xml not found
2023-10-09 15:42:21,213 INFO resource.ResourceUtils: Unable to find 'resource-types.xml'.
2023-10-09 15:42:21,620 INFO impl.YarnClientImpl: Submitted application application_1696837267350_0001
2023-10-09 15:42:21,743 INFO mapreduce.Job: The url to track the job: http://hadoop13:8088/proxy/application_1696837267350_0001/
2023-10-09 15:42:21,745 INFO mapreduce.Job: Running job: job_1696837267350_0001
2023-10-09 15:42:30,000 INFO mapreduce.Job: Job job_1696837267350_0001 running in uber mode : false
2023-10-09 15:42:30,002 INFO mapreduce.Job: map 0% reduce 0%
2023-10-09 15:42:32,053 INFO mapreduce.Job: Task Id : attempt_1696837267350_0001_m_000000_0, Status : FAILED
Container launch failed for container_e50_1696837267350_0001_01_000002 : org.apache.hadoop.yarn.exceptions.InvalidAuxServiceException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptionPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBImpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java:106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:163)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:42:33,087 INFO mapreduce.Job: Task Id : attempt_1696837267350_0001_m_000000_1, Status : FAILED
Container launch failed for container_e50_1696837267350_0001_01_000003 : org.apache.hadoop.yarn.exceptions.InvalidAuxServiceException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptionPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBImpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java:106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:163)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:42:35,113 INFO mapreduce.Job: Task Id : attempt_1696837267350_0001_m_000000_2, Status : FAILED
Container launch failed for container_e50_1696837267350_0001_01_000004 : org.apache.hadoop.yarn.exceptions.InvalidAuxServiceException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptionPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBImpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java:106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:163)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:42:38,147 INFO mapreduce.Job: map 100% reduce 100%
2023-10-09 15:42:39,167 INFO mapreduce.Job: Job job_1696837267350_0001 failed with state FAILED due to: Task failed task_1696837267350_0001_m_000000
Job failed as tasks failed. failedMaps:1 failedReduces:0 killedMaps:0 killedReduces: 0
2023-10-09 15:42:39,245 INFO mapreduce.Job: Counters: 10
Job Counters
Failed map tasks=4
Killed reduce tasks=1
Launched map tasks=4
Other local map tasks=3
Data-local map tasks=1
Total time spent by all maps in occupied slots (ms)=5
Total time spent by all reduces in occupied slots (ms)=0
Total time spent by all map tasks (ms)=5
Total vcore-milliseconds taken by all map tasks=5
Total megabyte-milliseconds taken by all map tasks=5120
[root@hadoop11 data]#
[root@hadoop11 data]# hadoop jar /opt/installs/hadoop3.1.4/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.4.jar pi 1 10
Number of Maps = 1
Samples per Map = 10
Wrote input for Map #0
Starting Job
2023-10-09 15:45:28,177 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /tmp/hadoop-yarn/staging/roo t/.staging/job_1696837267350_0002
2023-10-09 15:45:28,335 INFO input.FileInputFormat: Total input files to process : 1
2023-10-09 15:45:28,441 INFO mapreduce.JobSubmitter: number of splits:1
2023-10-09 15:45:28,629 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1696837267350_0002
2023-10-09 15:45:28,631 INFO mapreduce.JobSubmitter: Executing with tokens: []
2023-10-09 15:45:28,856 INFO conf.Configuration: resource-types.xml not found
2023-10-09 15:45:28,857 INFO resource.ResourceUtils: Unable to find 'resource-types.xml'.
2023-10-09 15:45:28,939 INFO impl.YarnClientImpl: Submitted application application_1696837267350_0002
2023-10-09 15:45:29,009 INFO mapreduce.Job: The url to track the job: http://hadoop13:8088/proxy/application_1696837267350_ 0002/
2023-10-09 15:45:29,011 INFO mapreduce.Job: Running job: job_1696837267350_0002
2023-10-09 15:45:36,147 INFO mapreduce.Job: Job job_1696837267350_0002 running in uber mode : false
2023-10-09 15:45:36,149 INFO mapreduce.Job: map 0% reduce 0%
2023-10-09 15:45:37,190 INFO mapreduce.Job: Task Id : attempt_1696837267350_0002_m_000000_0, Status : FAILED
Container launch failed for container_e50_1696837267350_0002_01_000002 : org.apache.hadoop.yarn.exceptions.InvalidAuxServic eException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptio nPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBI mpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java: 106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:16 3)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java: 394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:45:39,235 INFO mapreduce.Job: Task Id : attempt_1696837267350_0002_m_000000_1, Status : FAILED
Container launch failed for container_e50_1696837267350_0002_01_000003 : org.apache.hadoop.yarn.exceptions.InvalidAuxServic eException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptio nPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBI mpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java: 106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:16 3)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java: 394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:45:41,260 INFO mapreduce.Job: Task Id : attempt_1696837267350_0002_m_000000_2, Status : FAILED
Container launch failed for container_e50_1696837267350_0002_01_000004 : org.apache.hadoop.yarn.exceptions.InvalidAuxServic eException: The auxService:mapreduce_shuffle does not exist
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateExceptionImpl(SerializedExceptio nPBImpl.java:171)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.instantiateException(SerializedExceptionPBI mpl.java:182)
at org.apache.hadoop.yarn.api.records.impl.pb.SerializedExceptionPBImpl.deSerialize(SerializedExceptionPBImpl.java: 106)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:16 3)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java: 394)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2023-10-09 15:45:44,293 INFO mapreduce.Job: map 100% reduce 100%
2023-10-09 15:45:44,307 INFO mapreduce.Job: Job job_1696837267350_0002 failed with state FAILED due to: Task failed task_16 96837267350_0002_m_000000
Job failed as tasks failed. failedMaps:1 failedReduces:0 killedMaps:0 killedReduces: 0
2023-10-09 15:45:44,387 INFO mapreduce.Job: Counters: 10
Job Counters
Failed map tasks=4
Killed reduce tasks=1
Launched map tasks=4
Other local map tasks=3
Data-local map tasks=1
Total time spent by all maps in occupied slots (ms)=5
Total time spent by all reduces in occupied slots (ms)=0
Total time spent by all map tasks (ms)=5
Total vcore-milliseconds taken by all map tasks=5
Total megabyte-milliseconds taken by all map tasks=5120
Job job_1696837267350_0002 failed!
[root@hadoop11 data]#
最开始发现这个mr shuffle的报错是在beeline中执行走mr的查询代码时,发现程序不走mr,经过测试发现是hadoop中yarn的mr配置原因,因为我们服务器之前装hadoop的哥们只用spark,在服务器的yarn中只有spark的成功任务,从没跑过mr。问题已经很明确,环境配置缺少。
AWS EMR S3DistCp: The auxService:mapreduce_shuffle does not exist
网上有比较多的方案,这一篇的配置方法提到了spark的shuffle。