You may choose to install spark, yarn, hive, etc one by one. [Spark] 00 - Install Hadoop & Spark

But here, we will introduce how to install and configure big data environment in an automatic way. You will also understand why CDH is there.

一些资源

cdh的pyspark安装：https://blog.csdn.net/weixin_43215250/article/details/89186733

背景知识

Cluster

Ubuntu 18.04

node00, 192.168.56.1

CentOS 7.7

node01, 192.168.56.100

node02, 192.168.56.110

node03, 192.168.56.120

Packages

(base) [hadoop@node01 soft]$ ll

total

-rwxrwxrwx  hadoop hadoop   Nov  : Anaconda3-2019.07-Linux-x86_64.sh

-rw-r--r--  hadoop hadoop  Nov  : CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel

-rwxrwxr-x  hadoop hadoop          Nov  : CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.sha

-rw-r--r--  hadoop hadoop          Nov  : CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.sha1

-rw-r--r--  hadoop hadoop   Nov  : cloudera-manager-centos7-cm5.14.2_x86_64.tar.gz

-rw-rw-r--  hadoop hadoop   Nov  : jdk-8u202-linux-x64.tar.gz

-rw-r--r--  hadoop hadoop   Nov  : jdk-8u211-linux-x64.rpm

drwxr-xr-x  hadoop hadoop         Nov  : kafka parcel安装包

-rw-r--r--  hadoop hadoop       Nov  : manifest.json

-rw-r--r--  hadoop hadoop    Nov  : maxwell-1.22.1.tar.gz

-rw-r--r--  root   root         Apr     mysql57-community-release-el7-10.noarch.rpm

-rw-r--r--  hadoop hadoop      Nov  : mysql-connector-java.jar

-rw-rw-r--  hadoop hadoop    Nov  : zookeeper-3.4.5-cdh5.14.2.tar.gz

Data Pipeline

一、引出问题

QPS: Queries Per Second

单个表的大小达到400w-500w时，性能比较低下。开始 “分库、分表”。那岂不是要分太多的表？

- 辅助索引：只能局部有效。
- 分库策略：join方法不能用了；cout, order, group也不能用了。
- 扩容策略：需要再次水平拆分，迁移数据。

读写分离

Ref: 什么是数据库读写分离？

Ref: mysql数据库的主从同步，实现读写分离

大多数互联网业务，往往读多写少，这时候，数据库的读会首先称为数据库的瓶颈，这时，如果我们希望能够线性的提升数据库的读性能，消除读写锁冲突从而提升数据库的写性能，那么就可以使用“分组架构”（读写分离架构）。

用一句话概括，读写分离是用来解决数据库的读性能瓶颈的。

同时也带来一些问题：

- 数据库连接池要进行区分，哪些是读连接池，哪个是写连接池，研发的难度会增加；
- 为了保证高可用，读连接池要能够实现故障自动转移；
- 主从的一致性问题需要考虑。

缓存策略

如果在缓存的读写分离进行二选一时，还是应该首先考虑 "缓存"。

- 缓存的使用成本要比从库少非常多；
- 缓存的开发比较容易，大部分的读操作都可以先去缓存，找不到的再渗透到数据库。
- 当然，如果我们已经运用了缓存，但是读依旧还是瓶颈时，就可以选择“读写分离”架构了。简单来说，我们可以将读写分离看做是缓存都解决不了时的一种解决方案。
- 当然，缓存也不是没有缺点的：对于缓存，我们必须要考虑的就是高可用，不然，如果缓存一旦挂了，所有的流量都同时聚集到了数据库上，那么数据库是肯定会挂掉的。

水平切分

常见的，其实是数据容量的瓶颈。例如订单表，数据量只增不减，历史数据又必须要留存，非常容易成为性能的瓶颈。

数据库水平切分，也是一种常见的数据库架构，是一种通过算法，将数据库进行分割的架构。一个水平切分集群中的每个数据库，通常称为一个“分片”。每一个分片中的数据没有重合，所有分片中的数据并集组成全部数据。

二、数据工程的 "细节问题"

binlog的意义

分析数据时，不能影响主库。

主库 --> binlog文件 --> maxwell --> kalfa cluster --> hbaseMaster

把数据分析的业务脱离出来，缓解数据分析的 “读写压力” 。

hbase的使用问题

spark和hbase集成时默认进行的是全表扫描，给内存带来压力。

kafka的使用问题

kafka的偏移量管理，(1) 可能会导致一条消息被处理多次。(2) 至少被消费一次。

前后端分离

REST架构风格。

Goto: 理解本真的 REST 架构风格

Cloudera 集群搭建

一、Cloudera Manager

Server

　　--> Management Service

　　--> Database 

Agent

Agent

...

二、前期准备

三台机器执行如下命令。

防火墙

systemctl stop firewalld

systemctl disable firewalld

关闭selinux安全子系统

vim /etc/selinux/config

SELINUX=disabled

配置时区

Asia>China>beijing

cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime

同步时间

如果下面不成功，则先执行类似的命令：date -s '2019-11-11 11:55:55'

三台机器执行以下命令定时同步xxx云服务器时间

yum -y install ntpdate

crontab -e

*/ * * * * /usr/sbin/ntpdate time1.aliyun.com

Ubuntu 创建root用户；ssh 免密登录。

(base) hadoop@unsw-ThinkPad-T490:/kkb/soft$ su root

Password:

su: Authentication failure

(base) hadoop@unsw-ThinkPad-T490:/soft$ sudo passwd root

Enter new UNIX password:

Retype new UNIX password:

passwd: password updated successfully

(base) hadoop@unsw-ThinkPad-T490:/soft$ su

Password:

root@unsw-ThinkPad-T490:/soft#

准备 cloudera安装包，jdk包，依赖包（如下）

yum -y install chkconfig python bind-utils psmisc libxslt zlib sqlite cyrus-sasl-plain cyrus-sasl-gssapi fuse portmap fuse-libs redhat-lsb

三、配置MySQL的scm用户

MySQL数据库只安装在node02即可，放不同的node上。

[root@node02 ~]#  yum -y install mysql57-community-release-el7-10.noarch.rpm 

[root@node02 ~]# yum -y install mysql-community-server

# 已经查询不到mariadb数据库，被覆盖掉了。

[root@node02 ~]# rpm -qa|grep mariadb

You have new mail in /var/spool/mail/root

[服务] MySQL数据库设置。

[root@node02 hadoop]# systemctl start mysqld.service

[root@node02 hadoop]# systemctl status  mysqld.service

● mysqld.service - MySQL Server

   Loaded: loaded (/usr/lib/systemd/system/mysqld.service; enabled; vendor preset: disabled)

   Active: active (running) since Sun 2019-11-24 10:00:18 AEDT; 2h 58min ago

     Docs: man:mysqld(8)

           http://dev.mysql.com/doc/refman/en/using-systemd.html

 Main PID: 1311 (mysqld)

   CGroup: /system.slice/mysqld.service

           └─1311 /usr/sbin/mysqld --daemonize --pid-file=/var/run/mysqld/mysqld.pid

Nov 24 10:00:17 node02.kaikeba.com systemd[1]: Starting MySQL Server...

Nov 24 10:00:18 node02.kaikeba.com systemd[1]: Started MySQL Server.

添加root用户远程访问数据库。

[root@node02 ~]# mysql -u root -p

mysql> show databases;

+--------------------+

| Database           |

+--------------------+

| information_schema |

| maxwell            |

| mysql              |

| #mysql50#mysql-bin |

| performance_schema |

| scm                |

| sys                |

+--------------------+

7 rows in set (0.09 sec)

mysql> update mysql.user set Grant_priv='Y',Super_priv='Y' where user = 'root' and host = '%';
Query OK, 1 row affected (0.00 sec)

Rows matched: 1 Changed: 1 Warnings: 0



mysql> flush privileges;
Query OK, 0 rows affected (0.00 sec)

mysql> quit

[root@node02 ~]# systemctl restart mysqld.service

[root@node01 ~]# cp mysql-connector-java.jar /opt/cm-5.14.2/share/cmf/lib/

所有节点手动创建文件夹。

[root@node01 ~]# mkdir /opt/cm-5.14./run/cloudera-scm-agent

所有节点，创建cloudera-scm用户

useradd --system --home=/opt/cm-5.14./run/cloudera-scm-server --no-create-home --shell=/bin/false --comment "Cloudera SCM User" cloudera-scm

远程创建用户：scm。如果原数据库中有scm database，先删掉。再创建如下。

[root@node01 ~]# /opt/cm-5.14.2/share/cmf/schema/scm_prepare_database.sh mysql -h node02 -uroot -p'<pwd>' --scm-host node01 scm scm '<pwd>'

所有节点，设置好cloudera的master的位置。

[root@node01 ~]# vi /opt/cm-5.14./etc/cloudera-scm-agent/config.ini

[General]

# 修改成node01

server_host=node01

所有节点，添加cloudera-scm权限。

[root@node01 ~]# chown -R cloudera-scm:cloudera-scm /opt/cloudera

[root@node01 ~]# chown -R cloudera-scm:cloudera-scm /opt/cm-5.14.2

四、启动cloudera服务界面

[服务] node01启动服务。

[root@node01 ~]# /opt/cm-5.14./etc/init.d/cloudera-scm-server start

Starting cloudera-scm-server:                              [  OK  ]

等待直到7180端口出现。

[root@node01 opt]# ps -ef | grep scm-server

root     20411     1 77 15:17 pts/0    00:02:46 /kkb/install/jdk1.8.0_202/bin/java -cp .:lib/*:/usr/share/java/mysql-connector-java.jar:/usr/share/java/oracle-connector-java.jar -server -Dlog4j.configuration=file:/opt/cm-5.14.2/etc/cloudera-scm-server/log4j.properties -Dfile.encoding=UTF-8 -Dcmf.root.logger=INFO,LOGFILE -Dcmf.log.dir=/opt/cm-5.14.2/log/cloudera-scm-server -Dcmf.log.file=cloudera-scm-server.log -Dcmf.jetty.threshhold=WARN -Dcmf.schema.dir=/opt/cm-5.14.2/share/cmf/schema -Djava.awt.headless=true -Djava.net.preferIPv4Stack=true -Dpython.home=/opt/cm-5.14.2/share/cmf/python -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:+HeapDumpOnOutOfMemoryError -Xmx2G -XX:MaxPermSize=256m -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp -XX:OnOutOfMemoryError=kill -9 %p com.cloudera.server.cmf.Main

root     21270  9383  0 15:20 pts/0    00:00:00 grep --color=auto scm-server

[root@node01 opt]# netstat -anpl | grep 20411

tcp        0      0 0.0.0.0:7180            0.0.0.0:*               LISTEN      20411/java

tcp        0      0 0.0.0.0:7182            0.0.0.0:*               LISTEN      20411/java

tcp        0      0 192.168.56.100:7182     192.168.56.110:55332    ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47974    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:7182     192.168.56.100:42990    ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47230    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47228    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47972    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47976    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47234    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:7182     192.168.56.120:53120    ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47232    192.168.56.110:3306     ESTABLISHED 20411/java

tcp        0      0 192.168.56.100:47226    192.168.56.110:3306     ESTABLISHED 20411/java

unix  2      [ ]         STREAM     CONNECTED     81363    20411/java

unix  2      [ ]         STREAM     CONNECTED     82057    20411/java

[服务] 所有node启动agent。

[root@node01 ~]# /opt/cm-5.14./etc/init.d/cloudera-scm-agent start

Starting cloudera-scm-agent:                               [  OK  ]

登录管理界面，使用admin登录。常见问题如下。

Cloudera 安装Parcel提示主机运行状况不良

安装CDH时候出现主机运行状态不良情况的解决

安装CM+CDH 主机运行状况不良完美解决方案

注意下文件夹权限，删除这个cm_guid，重启agent服务就好了。

rm /opt/cm-5.14./lib/cloudera-scm-agent/cm_guid -rf

/opt/cm-5.14./etc/init.d/cloudera-scm-agent restart

如果半途中断，则reboot，关掉防火墙，删掉MySQL中的scm并重新创建，删除之前的分配数据，再开启server & agent。

[root@node01 ~]# hadoop jar /opt/cloudera/parcels/CDH-5.14.2-1.cdh5.14.2.p0.3/jars/hadoop-mapreduce-examples-2.6.0-cdh5.14.2.jar wordcount /test/words /test/output3

19/11/27 11:41:51 INFO client.RMProxy: Connecting to ResourceManager at node03.kaikeba.com/192.168.56.120:8032

19/11/27 11:41:52 INFO input.FileInputFormat: Total input paths to process : 1

19/11/27 11:41:52 INFO mapreduce.JobSubmitter: number of splits:1

19/11/27 11:41:52 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1574760305839_0002

19/11/27 11:41:52 INFO impl.YarnClientImpl: Submitted application application_1574760305839_0002

19/11/27 11:41:52 INFO mapreduce.Job: The url to track the job: http://node03.kaikeba.com:8088/proxy/application_1574760305839_0002/

19/11/27 11:41:52 INFO mapreduce.Job: Running job: job_1574760305839_0002

19/11/27 11:41:58 INFO mapreduce.Job: Job job_1574760305839_0002 running in uber mode : false

19/11/27 11:41:58 INFO mapreduce.Job:  map 0% reduce 0%

19/11/27 11:42:03 INFO mapreduce.Job:  map 100% reduce 0%

19/11/27 11:42:07 INFO mapreduce.Job:  map 100% reduce 100%

19/11/27 11:42:08 INFO mapreduce.Job: Job job_1574760305839_0002 completed successfully

19/11/27 11:42:08 INFO mapreduce.Job: Counters: 49

    File System Counters

        FILE: Number of bytes read=45

        FILE: Number of bytes written=298317

        FILE: Number of read operations=0

        FILE: Number of large read operations=0

        FILE: Number of write operations=0

        HDFS: Number of bytes read=119

        HDFS: Number of bytes written=17

        HDFS: Number of read operations=6

        HDFS: Number of large read operations=0

        HDFS: Number of write operations=2

    Job Counters

        Launched map tasks=1

        Launched reduce tasks=1

        Data-local map tasks=1

        Total time spent by all maps in occupied slots (ms)=2744

        Total time spent by all reduces in occupied slots (ms)=2409

        Total time spent by all map tasks (ms)=2744

        Total time spent by all reduce tasks (ms)=2409

        Total vcore-milliseconds taken by all map tasks=2744

        Total vcore-milliseconds taken by all reduce tasks=2409

        Total megabyte-milliseconds taken by all map tasks=2809856

        Total megabyte-milliseconds taken by all reduce tasks=2466816

    Map-Reduce Framework

        Map input records=1

        Map output records=2

        Map output bytes=21

        Map output materialized bytes=41

        Input split bytes=106

        Combine input records=2

        Combine output records=2

        Reduce input groups=2

        Reduce shuffle bytes=41

        Reduce input records=2

        Reduce output records=2

        Spilled Records=4

        Shuffled Maps =1

        Failed Shuffles=0

        Merged Map outputs=1

        GC time elapsed (ms)=121

        CPU time spent (ms)=1290

        Physical memory (bytes) snapshot=622190592

        Virtual memory (bytes) snapshot=5582626816

        Total committed heap usage (bytes)=505413632

    Shuffle Errors

        BAD_ID=0

        CONNECTION=0

        IO_ERROR=0

        WRONG_LENGTH=0

        WRONG_MAP=0

        WRONG_REDUCE=0

    File Input Format Counters

        Bytes Read=13

    File Output Format Counters

        Bytes Written=17

测试 hadoop - wordcount

五、单独安装Spark

可能自带的spark版本过低。

[root@node01 hadoop]# ls

manifest.json

SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904-el7.parcel

SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904-el7.parcel.sha1

SPARK2_ON_YARN-2.2.0.cloudera1.jar

[root@node01 hadoop]# ls /opt/cloudera/csd/

[root@node01 hadoop]# cp SPARK2_ON_YARN-2.2.0.cloudera1.jar /opt/cloudera/csd/

[root@node01 hadoop]# chown cloudera-scm:cloudera-scm /opt/cloudera/csd/SPARK2_ON_YARN-2.2.0.cloudera1.jar 

[root@node01 hadoop]# ls /opt/cloudera/csd/

SPARK2_ON_YARN-2.2.0.cloudera1.jar

[root@node01 hadoop]# ls /opt/cloudera/parcel-repo/

bap_manifest.json                               KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel          KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel.sha

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.sha      KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel.torrent

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.torrent  manifest.json

[root@node01 hadoop]# mv /opt/cloudera/parcel-repo/manifest.json /opt/cloudera/parcel-repo/manifest.json.bak

[root@node01 hadoop]# ls /opt/cloudera/parcel-repo/

bap_manifest.json                               KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel          KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel.sha

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.sha      KAFKA-3.1.0-1.3.1.0.p0.35-el7.parcel.torrent

CDH-5.14.2-1.cdh5.14.2.p0.3-el7.parcel.torrent  manifest.json.bak

[root@node01 hadoop]# cp SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904-el7.parcel  manifest.json /opt/cloudera/parcel-repo/

[root@node01 hadoop]#

先关掉集群，运行如下命令，再启动集群；如此，集群 -> parcel目录下能看到新增的spark2安装包，安装分配激活即可。

[root@node01 hadoop]# /opt/cm-5.14.2/etc/init.d/cloudera-scm-agent restart

Stopping cloudera-scm-agent:                               [  OK  ]

Starting cloudera-scm-agent:                               [  OK  ]

[root@node01 hadoop]# /opt/cm-5.14.2/etc/init.d/cloudera-scm-server restart

Stopping cloudera-scm-server:                              [  OK  ]

Starting cloudera-scm-server:                              [  OK  ]

Ref: CDH5.14.4离线安装Spark2.2.0详细步骤

还需要继续配置，依赖hadoop。

# 拷贝文件

cp /opt/cloudera/parcels/CDH/etc/spark/conf.dist/* /opt/cloudera/parcels/SPARK2/etc/spark2/conf.dist/

# 配置spark-env.sh文件

vim /opt/cloudera/parcels/SPARK2/etc/spark2/conf.dist/spark-env.sh

配置文件：/opt/cloudera/parcels/SPARK2/etc/spark2/conf.dist/spark-env.sh

SPARK_DIST_CLASSPATH="$SPARK_DIST_CLASSPATH:$(hadoop classpath)"

HADOOP_CONF_DIR=/etc/hadoop/conf

测试 spark 安装是否成功。

[root@node01 ~]# spark2-submit --deploy-mode client --conf spark.ui.port=4041 --class org.apache.spark.examples.SparkPi /opt/cloudera/parcels/SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904/lib/spark2/examples/jars/spark-examples_2.11-2.1.0.cloudera1.jar 10

19/11/27 13:56:58 INFO spark.SparkContext: Running Spark version 2.1.0.cloudera1

19/11/27 13:56:58 INFO spark.SecurityManager: Changing view acls to: root,hdfs

19/11/27 13:56:58 INFO spark.SecurityManager: Changing modify acls to: root,hdfs

19/11/27 13:56:58 INFO spark.SecurityManager: Changing view acls groups to:

19/11/27 13:56:58 INFO spark.SecurityManager: Changing modify acls groups to:

19/11/27 13:56:58 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(root, hdfs); groups with view permissions: Set(); users  with modify permissions: Set(root, hdfs); groups with modify permissions: Set()

19/11/27 13:56:59 INFO util.Utils: Successfully started service 'sparkDriver' on port 42324.

19/11/27 13:56:59 INFO spark.SparkEnv: Registering MapOutputTracker

19/11/27 13:56:59 INFO spark.SparkEnv: Registering BlockManagerMaster

19/11/27 13:56:59 INFO storage.BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information

19/11/27 13:56:59 INFO storage.BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up

19/11/27 13:56:59 INFO storage.DiskBlockManager: Created local directory at /tmp/blockmgr-006c0a44-497e-4cc6-b3bd-91c133c9fb83

19/11/27 13:56:59 INFO memory.MemoryStore: MemoryStore started with capacity 366.3 MB

19/11/27 13:56:59 INFO spark.SparkEnv: Registering OutputCommitCoordinator

19/11/27 13:56:59 INFO util.log: Logging initialized @2260ms

19/11/27 13:56:59 INFO server.Server: jetty-9.2.z-SNAPSHOT

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@791cbf87{/jobs,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@a7e2d9d{/jobs/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@754777cd{/jobs/job,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2b52c0d6{/jobs/job/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@372ea2bc{/stages,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4cc76301{/stages/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2f08c4b{/stages/stage,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3f19b8b3{/stages/stage/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7de0c6ae{/stages/pool,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@a486d78{/stages/pool/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@cdc3aae{/storage,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7ef2d7a6{/storage/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5dcbb60{/storage/rdd,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4c36250e{/storage/rdd/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@21526f6c{/environment,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@49f5c307{/environment/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@299266e2{/executors,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5471388b{/executors/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@66ea1466{/executors/threadDump,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1601e47{/executors/threadDump/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3bffddff{/static,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@66971f6b{/,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@50687efb{/api,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@517bd097{/jobs/job/kill,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@142eef62{/stages/stage/kill,null,AVAILABLE}

19/11/27 13:56:59 INFO server.ServerConnector: Started ServerConnector@e6516e{HTTP/1.1}{0.0.0.0:4041}

19/11/27 13:56:59 INFO server.Server: Started @2384ms

19/11/27 13:56:59 INFO util.Utils: Successfully started service 'SparkUI' on port 4041.

19/11/27 13:56:59 INFO ui.SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.56.100:4041

19/11/27 13:56:59 INFO spark.SparkContext: Added JAR file:/opt/cloudera/parcels/SPARK2-2.1.0.cloudera1-1.cdh5.7.0.p0.120904/lib/spark2/examples/jars/spark-examples_2.11-2.1.0.cloudera1.jar at spark://192.168.56.100:42324/jars/spark-examples_2.11-2.1.0.cloudera1.jar with timestamp 1574823419519

19/11/27 13:56:59 INFO executor.Executor: Starting executor ID driver on host localhost

19/11/27 13:56:59 INFO util.Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 33556.

19/11/27 13:56:59 INFO netty.NettyBlockTransferService: Server created on 192.168.56.100:33556

19/11/27 13:56:59 INFO storage.BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy

19/11/27 13:56:59 INFO storage.BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.56.100, 33556, None)

19/11/27 13:56:59 INFO storage.BlockManagerMasterEndpoint: Registering block manager 192.168.56.100:33556 with 366.3 MB RAM, BlockManagerId(driver, 192.168.56.100, 33556, None)

19/11/27 13:56:59 INFO storage.BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.56.100, 33556, None)

19/11/27 13:56:59 INFO storage.BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.56.100, 33556, None)

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@24e8de5c{/metrics/json,null,AVAILABLE}

19/11/27 13:56:59 INFO internal.SharedState: Warehouse path is 'file:/root/spark-warehouse/'.

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2f6bcf87{/SQL,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@78c7f9b3{/SQL/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@e93f3d5{/SQL/execution,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7a26928a{/SQL/execution/json,null,AVAILABLE}

19/11/27 13:56:59 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@73eb8672{/static/sql,null,AVAILABLE}

19/11/27 13:57:00 INFO spark.SparkContext: Starting job: reduce at SparkPi.scala:38

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Got job 0 (reduce at SparkPi.scala:38) with 10 output partitions

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Final stage: ResultStage 0 (reduce at SparkPi.scala:38)

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Parents of final stage: List()

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Missing parents: List()

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34), which has no missing parents

19/11/27 13:57:00 INFO memory.MemoryStore: Block broadcast_0 stored as values in memory (estimated size 1832.0 B, free 366.3 MB)

19/11/27 13:57:00 INFO memory.MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1172.0 B, free 366.3 MB)

19/11/27 13:57:00 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.56.100:33556 (size: 1172.0 B, free: 366.3 MB)

19/11/27 13:57:00 INFO spark.SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:996

19/11/27 13:57:00 INFO scheduler.DAGScheduler: Submitting 10 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34)

19/11/27 13:57:00 INFO scheduler.TaskSchedulerImpl: Adding task set 0.0 with 10 tasks

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, executor driver, partition 0, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, localhost, executor driver, partition 1, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 2.0 in stage 0.0 (TID 2, localhost, executor driver, partition 2, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Running task 0.0 in stage 0.0 (TID 0)

19/11/27 13:57:01 INFO executor.Executor: Running task 1.0 in stage 0.0 (TID 1)

19/11/27 13:57:01 INFO executor.Executor: Fetching spark://192.168.56.100:42324/jars/spark-examples_2.11-2.1.0.cloudera1.jar with timestamp 1574823419519

19/11/27 13:57:01 INFO executor.Executor: Running task 2.0 in stage 0.0 (TID 2)

19/11/27 13:57:01 INFO client.TransportClientFactory: Successfully created connection to /192.168.56.100:42324 after 57 ms (0 ms spent in bootstraps)

19/11/27 13:57:01 INFO util.Utils: Fetching spark://192.168.56.100:42324/jars/spark-examples_2.11-2.1.0.cloudera1.jar to /tmp/spark-185ac05b-8163-4178-b316-b1081fa7cf76/userFiles-bf97f19c-518c-4bb9-aefe-2b67ab152467/fetchFileTemp69449570899073492.tmp

19/11/27 13:57:01 INFO executor.Executor: Adding file:/tmp/spark-185ac05b-8163-4178-b316-b1081fa7cf76/userFiles-bf97f19c-518c-4bb9-aefe-2b67ab152467/spark-examples_2.11-2.1.0.cloudera1.jar to class loader

19/11/27 13:57:01 INFO executor.Executor: Finished task 1.0 in stage 0.0 (TID 1). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO executor.Executor: Finished task 0.0 in stage 0.0 (TID 0). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO executor.Executor: Finished task 2.0 in stage 0.0 (TID 2). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 3.0 in stage 0.0 (TID 3, localhost, executor driver, partition 3, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Running task 3.0 in stage 0.0 (TID 3)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 4.0 in stage 0.0 (TID 4, localhost, executor driver, partition 4, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Running task 4.0 in stage 0.0 (TID 4)

19/11/27 13:57:01 INFO executor.Executor: Finished task 4.0 in stage 0.0 (TID 4). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 5.0 in stage 0.0 (TID 5, localhost, executor driver, partition 5, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Finished task 3.0 in stage 0.0 (TID 3). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO executor.Executor: Running task 5.0 in stage 0.0 (TID 5)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 6.0 in stage 0.0 (TID 6, localhost, executor driver, partition 6, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 7.0 in stage 0.0 (TID 7, localhost, executor driver, partition 7, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Running task 7.0 in stage 0.0 (TID 7)

19/11/27 13:57:01 INFO executor.Executor: Finished task 5.0 in stage 0.0 (TID 5). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO executor.Executor: Running task 6.0 in stage 0.0 (TID 6)

19/11/27 13:57:01 INFO executor.Executor: Finished task 6.0 in stage 0.0 (TID 6). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO executor.Executor: Finished task 7.0 in stage 0.0 (TID 7). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 629 ms on localhost (executor driver) (1/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 8.0 in stage 0.0 (TID 8, localhost, executor driver, partition 8, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Starting task 9.0 in stage 0.0 (TID 9, localhost, executor driver, partition 9, PROCESS_LOCAL, 6036 bytes)

19/11/27 13:57:01 INFO executor.Executor: Running task 8.0 in stage 0.0 (TID 8)

19/11/27 13:57:01 INFO executor.Executor: Running task 9.0 in stage 0.0 (TID 9)

19/11/27 13:57:01 INFO executor.Executor: Finished task 9.0 in stage 0.0 (TID 9). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 759 ms on localhost (executor driver) (2/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 5.0 in stage 0.0 (TID 5) in 129 ms on localhost (executor driver) (3/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 6.0 in stage 0.0 (TID 6) in 105 ms on localhost (executor driver) (4/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 7.0 in stage 0.0 (TID 7) in 104 ms on localhost (executor driver) (5/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 9.0 in stage 0.0 (TID 9) in 52 ms on localhost (executor driver) (6/10)

19/11/27 13:57:01 INFO executor.Executor: Finished task 8.0 in stage 0.0 (TID 8). 1041 bytes result sent to driver

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 2.0 in stage 0.0 (TID 2) in 721 ms on localhost (executor driver) (7/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 4.0 in stage 0.0 (TID 4) in 149 ms on localhost (executor driver) (8/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 3.0 in stage 0.0 (TID 3) in 168 ms on localhost (executor driver) (9/10)

19/11/27 13:57:01 INFO scheduler.TaskSetManager: Finished task 8.0 in stage 0.0 (TID 8) in 59 ms on localhost (executor driver) (10/10)

19/11/27 13:57:01 INFO scheduler.DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:38) finished in 0.801 s

19/11/27 13:57:01 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool

19/11/27 13:57:01 INFO scheduler.DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 1.254717 s

Pi is roughly 3.1406751406751408

19/11/27 13:57:01 INFO server.ServerConnector: Stopped ServerConnector@e6516e{HTTP/1.1}{0.0.0.0:4041}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@142eef62{/stages/stage/kill,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@517bd097{/jobs/job/kill,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@50687efb{/api,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@66971f6b{/,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@3bffddff{/static,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@1601e47{/executors/threadDump/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@66ea1466{/executors/threadDump,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@5471388b{/executors/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@299266e2{/executors,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@49f5c307{/environment/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@21526f6c{/environment,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@4c36250e{/storage/rdd/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@5dcbb60{/storage/rdd,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@7ef2d7a6{/storage/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@cdc3aae{/storage,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@a486d78{/stages/pool/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@7de0c6ae{/stages/pool,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@3f19b8b3{/stages/stage/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@2f08c4b{/stages/stage,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@4cc76301{/stages/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@372ea2bc{/stages,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@2b52c0d6{/jobs/job/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@754777cd{/jobs/job,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@a7e2d9d{/jobs/json,null,UNAVAILABLE}

19/11/27 13:57:01 INFO handler.ContextHandler: Stopped o.s.j.s.ServletContextHandler@791cbf87{/jobs,null,UNAVAILABLE}

19/11/27 13:57:01 INFO ui.SparkUI: Stopped Spark web UI at http://192.168.56.100:4041

19/11/27 13:57:01 INFO spark.MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!

19/11/27 13:57:01 INFO memory.MemoryStore: MemoryStore cleared

19/11/27 13:57:01 INFO storage.BlockManager: BlockManager stopped

19/11/27 13:57:02 INFO storage.BlockManagerMaster: BlockManagerMaster stopped

19/11/27 13:57:02 INFO scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!

19/11/27 13:57:02 INFO spark.SparkContext: Successfully stopped SparkContext

19/11/27 13:57:02 INFO util.ShutdownHookManager: Shutdown hook called

19/11/27 13:57:02 INFO util.ShutdownHookManager: Deleting directory /tmp/spark-185ac05b-8163-4178-b316-b1081fa7cf76

spark test log

六、图形管理界面 Kafka Manager

Download: https://github.com/yahoo/kafka-manager/archive/1.3.1.6.zip

Goto: kafka-manager的安装与配置

启动后登录：http://192.168.56.100:8080/，设置cluster name, Cluster Zookeeper Hosts后，保存即可。图形化管理Kafka配置。

[root@node01 kafka-manager-1.3.1.6]# ls

bin  conf  lib  README.md  share

[root@node01 kafka-manager-1.3.1.6]# nohup  bin/kafka-manager -Dconfig.file=conf/application.conf -Dhttp.port=8080  &

[1] 4115

[root@node01 kafka-manager-1.3.1.6]# nohup: ignoring input and appending output to ‘nohup.out’

[root@node01 kafka-manager-1.3.1.6]#

[root@node01 kafka-manager-1.3.1.6]# netstat -ano|grep 8080

tcp6       0      0 :::8080                 :::*                    LISTEN      off (0.00/0/0)

七、分布式缓存 Redis

Ref: 同为分布式缓存，为何Redis更胜一筹？

Ref: 为什么分布式一定要有redis?

先编译，然后将编译结果拷贝到 /usr/local 下面。

make

make test

mkdir -p /usr/local/redis/bin

mkdir -p /usr/local/redis/etc


cd ./src

cp redis-cli redis-server mkreleasehdr.sh redis-check-aof redis-check-dump redis-benchmark /usr/local/redis/bin
cp ../redis.conf /usr/local/redis/etc

编辑 redis.conf文件：

将daemonize选项由no置为yes,使redis能后台运行。

注释掉bind 127.0.0.1,将它改为bind 0.0.0.0, protected-mode yes 改为 protected-mode no (这个3.2版本以后才有)。

[root@node01 bin]#

[root@node01 bin]#

[root@node01 bin]# pwd

/usr/local/redis/bin

[root@node01 bin]# ./redis-server ../etc/redis.conf

31444:C 27 Nov 10:48:10.708 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo

31444:C 27 Nov 10:48:10.708 # Redis version=4.0.11, bits=64, commit=00000000, modified=0, pid=31444, just started

31444:C 27 Nov 10:48:10.708 # Configuration loaded

如果还是连不上，那肯定是你的服务器后台安全组设置没有吧6379放行；

systemctl stop firewalld.service

systemctl stop iptables.service

End.

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[CDH] Cloudera's Distribution including Apache Hadoop