作者归档：xinlu

关于xinlu

人生本来就是一场修行...

普通用户也可重启nginx

1.修改nginx.conf为abc:root启动

  user  abc abc;  #以普通用户启，但实际上是master为root,worker进程是abc。
或 
  user abc root;

2.修改nginx

chown root nginx #nginx必须是root用户拥有者。
chmod a+s nginx  #把x属性改为s属性。
ll nginx
-rwsr-sr-x 1 root root 2030760 Mar  5 11:52 nginx

阿里云Docker私人专属镜像加速

https://cr.console.aliyun.com/cn-hangzhou/instances/mirrors

{
“bip”:”192.168.55.1/24″,
“registry-mirrors”: [“https://2na48vbddcw.mirror.aliyuncs.com”]
}

把我常用的字母移除到只有8个字母。
sudo systemctl daemon-reload
sudo systemctl restart docker

HIVE的sequenceFile的操作常用命令

sequencefile是一组Key和Value的健值对。在实际中HIVE创建表时，key是没有无意义的。它只根据value的格式进行切换数据。
0.登录容器并连接上hive

docker-compose -f docker-compose-hive.yml exec hive-server  bash
/opt/hive/bin/beeline -u jdbc:hive2://localhost:10000

1.建表

 
create external table sfgz(
     `idx` string,
     `userid` string,
     `flag` string,
     `count` string,
     `value` string,
     `memo` string)
  partitioned by (dt string)
  row format delimited fields terminated by ','
  stored as sequencefile
  location '/user/sfgz';

2.分区加载
方法一：
hadoop fs -mkdir -p /user/sfgz/dt=2010-05-06/
hadoop fs -put /tools/mytest.txt.sf /user/sfgz/dt=2019-05-17
hadoop fs -put /tools/mytest.txt.sf /user/sfgz/dt=2010-05-04
这样是无法直接被hive所识别的，必须用alter table partition的命令把相应的分区表加入至数据库中，才能正常访问。
方法二，加载完就可以直接查询的：
load data local inpath ‘/tools/mytest.txt.sf’ into table sfgz partition(dt=’2009-03-01′);这种方法是可以直接查询了。
load data local inpath ‘/tools/mytest.gzip.sf’ into table sfgz partition(dt=’2000-03-02′);
3. 检查分区信息：
show partitions sfgz;
4. 添加分区
alter table sfgz add partition(dt=’2000-03-03′);
5. 插入一条记录：

   insert into sfgz partition(dt='2019-05-16')values('idx3','uid6','5','6','34.7','uid3test2');

6. 统计指令：
select count(*) from sfgz; 在KMR中不支持这种方式。
select count(idx) from sfgz; 在KMR中只支持这种方式。
6. 其它常见命令
show databases;
use database;
whow tables;
select * from sfgz where dt=’2000-03-03′;
msck repair table sfgz; 分区修复指令：

docker-hive的操作验试

1.下载docker镜像库：https://github.com/big-data-europe/docker-hive.git，并安装它。
2.修改其docker-compose.yml文件，为每个容器增加上映射。

version: "3"
 
services:
  namenode:
    image: bde2020/hadoop-namenode:2.0.0-hadoop2.7.4-java8
    volumes:
      - /data/namenode:/hadoop/dfs/name
      - /data/tools:/tools
    environment:
      - CLUSTER_NAME=test
    env_file:
      - ./hadoop-hive.env
    ports:
      - "50070:50070"
  datanode:
    image: bde2020/hadoop-datanode:2.0.0-hadoop2.7.4-java8
    volumes:
      - /data/datanode:/hadoop/dfs/data
      - /data/tools:/tools
    env_file:
      - ./hadoop-hive.env
    environment:
      SERVICE_PRECONDITION: "namenode:50070"
    ports:
      - "50075:50075"
  hive-server:
    image: bde2020/hive:2.3.2-postgresql-metastore
    volumes:
      - /data/tools:/tools
    env_file:
      - ./hadoop-hive.env
    environment:
      HIVE_CORE_CONF_javax_jdo_option_ConnectionURL: "jdbc:postgresql://hive-metastore/metastore"
      SERVICE_PRECONDITION: "hive-metastore:9083"
    ports:
      - "10000:10000"
  hive-metastore:
    image: bde2020/hive:2.3.2-postgresql-metastore
    volumes:
      - /data/tools:/tools
    env_file:
      - ./hadoop-hive.env
    command: /opt/hive/bin/hive --service metastore
    environment:
      SERVICE_PRECONDITION: "namenode:50070 datanode:50075 hive-metastore-postgresql:5432"
    ports:
      - "9083:9083"
  hive-metastore-postgresql:
    image: bde2020/hive-metastore-postgresql:2.3.0
    volumes:
      - /data/tools:/tools
 
  presto-coordinator:
    image: shawnzhu/prestodb:0.181
    volumes:
      - /data/tools:/tools
    ports:
      - "8080:8080"

2.创建测试文本

1,xiaoming,book-TV-code,beijing:chaoyang-shagnhai:pudong
2,lilei,book-code,nanjing:jiangning-taiwan:taibei
3,lihua,music-book,heilongjiang:haerbin
3,lihua,music-book,heilongjiang2:haerbin2
3,lihua,music-book,heilongjiang3:haerbin3

3.启动并连接HIVE服务。

docker-compose up -d
docker-compose exec hive-server bash
/opt/hive/bin/beeline -u jdbc:hive2://localhost:10000

4.创建外部表

create external table t2(
    id      int
   ,name    string
   ,hobby   array<string>
   ,add     map<String,string>
)
row format delimited
fields terminated by ','
collection items terminated by '-'
map keys terminated by ':'
location '/user/t2'

5.文件上传到上步骤中的目录内。
方法1：在HIVE的beeline终端中采用：
load data local inpath ‘/tools/example.txt’ overwrite into table t2; 删除已经存在的所有文件，然后写入新的文件。
load data local inpath ‘/tools/example.txt’ into table t2; 在目录中加入新的文件【差异在overwrite】。
方法2：用hadoop fs -put的文件上传功能。
hadoop fs -put /tools/example.txt /user/t2 文件名不改变。
hadoop fs -put /tools/example.txt /user/t2/1.txt 文件名为1.txt
6.在HIVE命令行中验证

select * from t2;  上传一次文件，执行一次。

7.在hadoop的文件管理器，也可以浏览到新上传的文件。

同一个文件中的记录是会自动作去重处理的。

——————————————-
如果是sequencefile呢？
1.检验sequencefile的内容。
hadoop fs -Dfs.default.name=file:/// -text /tools/mytest.gzip.sf 废弃的
hadoop fs -Dfs.defaultFS=file:/// -text /tools/mytest.txt.sf

实际内容是：

2.建表

  create external table sfgz(
     `idx` string,
     `userid` string,
     `flag` string,
     `count` string,
     `value` string,
     `memo` string)
  partitioned by (dt string)
  row format delimited fields terminated by ','
  stored as sequencefile
  location '/user/sfgz';

3.上传文件

方法一：
hadoop fs -mkdir -p /user/sfgz/dt=2010-05-06/
hadoop fs -put /tools/mytest.txt.sf /user/sfgz/dt=2019-05-17
hadoop fs -put /tools/mytest.txt.sf /user/sfgz/dt=2010-05-04
这种方法，还需要人为Reload一下才行，其reload指令是：
方法二：
load data local inpath '/tools/mytest.txt.sf' into table sfgz partition(dt='2009-03-01');这种方法是可以直接查询了。
load data local inpath '/tools/mytest.gzip.sf' into table sfgz partition(dt='2000-03-02');

spark/hive的镜像Github

Big Data Europe
目前最靠谱的样板
https://github.com/big-data-europe/docker-spark
https://github.com/big-data-europe/docker-hive
https://github.com/big-data-europe

HIVE文档
https://cwiki.apache.org/confluence/display/Hive/Home#Home-UserDocumentation

七牛日志分析

七牛日志格式

116.231.10.133 HIT 0 [07/May/2019:09:04:56 +0800] "GET http://wdl1.cache.wps.cn/per-plugin/dl/addons/pool/win-i386/wpsminisite_3.0.0.37.7z HTTP/1.1" 206 66372 "-" "-"

Qt的相关代码

int getDownloadSize(QString line) {
    int idx = line.indexOf("HTTP/1.1\"");
    if(idx > 0) {
        QString sub = line.mid(idx);
        QStringList sets = sub.split(" ");
        int size = sets.at(2).toInt();
        return size;
    }
    return 0;
}
 
 
int main(int argc, char *argv[])
{
    QCoreApplication a(argc, argv);
 
    QString dpath("F:\\日志0508\\18");
 
    QDir d(dpath);
    QStringList fs = d.entryList();
    qint64 plug_total = 1;
    qint64 other_total = 1;
    for(int i = 0; i < fs.size(); i++) {
        QString f = fs.at(i);
        QFile file(dpath+"\\"+f);
        if(!file.open(QIODevice::ReadOnly|QIODevice::Text)) {
            continue;
        }
        int linecnt = 0;
        while(!file.atEnd()) {
            QByteArray line = file.readLine();
            if(line.indexOf("wdl1.cache.wps.cn") < 0) {
                continue;
            }
            int idx = line.indexOf("win-i386");
            int size = getDownloadSize(line);
            qint64 skidx = file.pos();
            if(idx > 0) {
                plug_total += size;
            }else{
                other_total += size;
            }
            linecnt++;
            if(linecnt % 10000 == 0) {
                printf("\r\nlinecnt:%d - skidx:%lld - plug_total:%lld - other_total:%lld - ratio:%5f", linecnt, skidx, plug_total, other_total, double(plug_total) / double(other_total));
            }
        }
        printf("\r\nlinecnt:%d - plug_total:%lld - other_total:%lld - ratio:%5f", linecnt, plug_total, other_total, double(plug_total) / double(other_total));
    }
    printf("\r\nplug_total:%lld - other_total:%lld - ratio:%5f", plug_total, other_total, double(plug_total) / double(other_total));
    return a.exec();
}

获取响应内容

log_format cntr escape=json '{"time":"$time_local",'
                        '"@source":"$server_addr",'
                        '"hostname":"$hostname",'
                        '"xforward":"$http_x_forwarded_for",'
                        '"remoteaddr":"$remote_addr",'
                        '"method":"$request_method",'
                        '"scheme":"$scheme",'
                        '"domain":"$server_name",'
                        '"referer":"$http_referer",'
                        '"requrl":"$request_uri",'
                        '"args":"$args",'
                        '"requestbody":"$request_body",'
                        '"contentlength":"$content_length",'
                        '"bodybytessend":$body_bytes_sent,'
                        '"status":$status,'
                        '"requesttime":$request_time,'
                        '"upstreamtime":"$upstream_response_time",'
                        '"upstreamaddr":"$upstream_addr",'
                        '"respbody":"$resp_body",'
                        '"respdown":"$resp_ctrl_down",'
                        '"useragent":"$http_user_agent"'
                        '}';
location /abc {
        #access_log off;
        access_log /data/logs/nginx/abc/access.log cntr buffer=32k flush=5s;
        error_log /data/logs/nginx/abc/error.log info;
 
        set $resp_ctrl_down -1;
        set $resp_body "";
        # only elk collection machine, can add the below lua code.
        body_filter_by_lua_block {
            local chunk, eof = ngx.arg[1], ngx.arg[2]
            ngx.var.resp_body=ngx.var.resp_body..chunk
            if eof then
               if string.find(ngx.var.resp_body,'"count":true') then
                  ngx.var.resp_ctrl_down = 1
               else
                  ngx.var.resp_ctrl_down = 0
               end
            end
        }
 
        proxy_pass http://abc/flow;
    }

Centos7屏蔽防火墙

systemctl stop firewalld.service
systemctl disable firewalld.service

nginx日志格式

access_log path [format [buffer=size] [gzip[=level]] [flush=time] [if=condition]]; # 设置访问日志
access_log off; # 关闭访问日志

GoLang可靠内嵌数据库

https://github.com/boltdb/bolt

开心&努力

心路：人生的质量源自于精神的“法喜充满”