【数仓项目】百尺竿头,更进一步-dwd层构建

本文主要介绍dwd层数据构建

start处理
建表：

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hive (gmall)>
drop table if exists dwd_start_log;
CREATE EXTERNAL TABLE dwd_start_log(
`mid_id` string,
`user_id` string,
`version_code` string,
`version_name` string,
`lang` string,
`source` string,
`os` string,
`area` string,
`model` string,
`brand` string,
`sdk_version` string,
`gmail` string,
`height_width` string, 
`app_time` string,
`network` string,
`lng` string,
`lat` string,
`entry` string,
`open_ad_type` string,
`action` string,
`loading_time` string,
`detail` string,
`extend1` string
)
PARTITIONED BY (dt string)
location '/warehouse/gmall/dwd/dwd_start_log/';

导入数据：

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insert overwrite table dwd_start_log
PARTITION (dt='2019-02-10')
select
    get_json_object(line,'$.mid') mid_id,
    get_json_object(line,'$.uid') user_id,
    get_json_object(line,'$.vc') version_code,
    get_json_object(line,'$.vn') version_name,
    get_json_object(line,'$.l') lang,
    get_json_object(line,'$.sr') source,
    get_json_object(line,'$.os') os,
    get_json_object(line,'$.ar') area,
    get_json_object(line,'$.md') model,
    get_json_object(line,'$.ba') brand,
    get_json_object(line,'$.sv') sdk_version,
    get_json_object(line,'$.g') gmail,
    get_json_object(line,'$.hw') height_width,
    get_json_object(line,'$.t') app_time,
    get_json_object(line,'$.nw') network,
    get_json_object(line,'$.ln') lng,
    get_json_object(line,'$.la') lat,
    get_json_object(line,'$.entry') entry,
    get_json_object(line,'$.open_ad_type') open_ad_type,
    get_json_object(line,'$.action') action,
    get_json_object(line,'$.loading_time') loading_time,
    get_json_object(line,'$.detail') detail,
    get_json_object(line,'$.extend1') extend1
from ods_start_log
where dt='2019-02-10';

难点：event部分：

由于ods_event_log数据是日志数据，结构复杂，是json嵌套结构，所以需要自己定义一个udf和一个udtf函数来对其进行导入数据处理

先 建表：

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drop table if exists dwd_base_event_log;
CREATE EXTERNAL TABLE dwd_base_event_log(
`mid_id` string,
`user_id` string,
`version_code` string,
`version_name` string,
`lang` string,
`source` string,
`os` string,
`area` string,
`model` string,
`brand` string,
`sdk_version` string,
`gmail` string,
`height_width` string,
`app_time` string,
`network` string,
`lng` string,
`lat` string,
`event_name` string,
`event_json` string,
`server_time` string)
PARTITIONED BY (`dt` string)
stored as parquet
location '/warehouse/gmall/dwd/dwd_base_event_log/';

函数编写：

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maven：
<properties>
    <project.build.sourceEncoding>UTF8</project.build.sourceEncoding>
    <hive.version>1.2.1</hive.version>
</properties>

<dependencies>
    <!--添加hive依赖-->
    <dependency>
        <groupId>org.apache.hive</groupId>
        <artifactId>hive-exec</artifactId>
        <version>${hive.version}</version>
    </dependency>
</dependencies>

<build>
    <plugins>
        <plugin>
            <artifactId>maven-compiler-plugin</artifactId>
            <version>2.3.2</version>
            <configuration>
                <source>1.8</source>
                <target>1.8</target>
            </configuration>
        </plugin>
        <plugin>
            <artifactId>maven-assembly-plugin</artifactId>
            <configuration>
                <descriptorRefs>
                    <descriptorRef>jar-with-dependencies</descriptorRef>
                </descriptorRefs>
            </configuration>
            <executions>
                <execution>
                    <id>make-assembly</id>
                    <phase>package</phase>
                    <goals>
                        <goal>single</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
    </plugins>
</build>

UDF：

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package com.sumiya.udf;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.hive.ql.exec.UDF;
import org.json.JSONException;
import org.json.JSONObject;

public class BaseFieldUDF extends UDF {
    public String evaluate(String line,String jsonkeysString) {

        StringBuilder sb = new StringBuilder();

        //1.获取所有key，比如mid，uv，extend1等等
        String[] jsonkeys = jsonkeysString.split(",");

        //2.切割  服务器时间|json
        String[] logContents = line.split("\\|");

        //3.校验
        if (logContents.length != 2 || StringUtils.isBlank(logContents[1])) {
            return "";
        }


        try {
            //4.对logContent创建json
            JSONObject jsonObject = new JSONObject(logContents[1]);

            //5.获取公共字段的json对象
            JSONObject cmJson = jsonObject.getJSONObject("cm");
            //6.循环遍历
            for (String jsonkey : jsonkeys) {
                 jsonkey = jsonkey.trim();
                 if(cmJson.has(jsonkey)){
                     sb.append(cmJson.getString(jsonkey)).append("\t");
                 }else{
                     sb.append("\t");
                 }
            }
            //7.拼接事件字段和服务器时间
            sb.append(jsonObject.getString("et")).append("\t");
            sb.append(logContents[0]).append("\t");
        } catch (JSONException e) {
            e.printStackTrace();
        }
        return sb.toString();
    }

    //测试代码
    public static void main(String[] args) {

        String line = "1541217850324|{\"cm\":{\"mid\":\"m7856\",\"uid\":\"u8739\",\"ln\":\"-74.8\",\"sv\":\"V2.2.2\",\"os\":\"8.1.3\",\"g\":\"P7XC9126@gmail.com\",\"nw\":\"3G\",\"l\":\"es\",\"vc\":\"6\",\"hw\":\"640*960\",\"ar\":\"MX\",\"t\":\"1541204134250\",\"la\":\"-31.7\",\"md\":\"huawei-17\",\"vn\":\"1.1.2\",\"sr\":\"O\",\"ba\":\"Huawei\"},\"ap\":\"weather\",\"et\":[{\"ett\":\"1541146624055\",\"en\":\"display\",\"kv\":{\"goodsid\":\"n4195\",\"copyright\":\"ESPN\",\"content_provider\":\"CNN\",\"extend2\":\"5\",\"action\":\"2\",\"extend1\":\"2\",\"place\":\"3\",\"showtype\":\"2\",\"category\":\"72\",\"newstype\":\"5\"}},{\"ett\":\"1541213331817\",\"en\":\"loading\",\"kv\":{\"extend2\":\"\",\"loading_time\":\"15\",\"action\":\"3\",\"extend1\":\"\",\"type1\":\"\",\"type\":\"3\",\"loading_way\":\"1\"}},{\"ett\":\"1541126195645\",\"en\":\"ad\",\"kv\":{\"entry\":\"3\",\"show_style\":\"0\",\"action\":\"2\",\"detail\":\"325\",\"source\":\"4\",\"behavior\":\"2\",\"content\":\"1\",\"newstype\":\"5\"}},{\"ett\":\"1541202678812\",\"en\":\"notification\",\"kv\":{\"ap_time\":\"1541184614380\",\"action\":\"3\",\"type\":\"4\",\"content\":\"\"}},{\"ett\":\"1541194686688\",\"en\":\"active_background\",\"kv\":{\"active_source\":\"3\"}}]}";
        String x = new BaseFieldUDF().evaluate(line, "mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,nw,ln,la,t");
        System.out.println(x);
    }
}

UDTF：

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package com.sumiya.udtf;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDTF;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
import org.json.JSONArray;
import org.json.JSONException;

import java.util.ArrayList;
import java.util.List;

public class EventJsonUDTF extends GenericUDTF {

    @Deprecated
    public StructObjectInspector initialize(ObjectInspector[] argOIs)
            throws UDFArgumentException {
        List<String> filedNames = new ArrayList<>();
        List<ObjectInspector> filedType = new ArrayList<>();

        filedNames.add("event_name");
        filedType.add(PrimitiveObjectInspectorFactory.javaStringObjectInspector);
        filedNames.add("event_json");
        filedType.add(PrimitiveObjectInspectorFactory.javaStringObjectInspector);

        return ObjectInspectorFactory.getStandardStructObjectInspector(filedNames,filedType);
    }

    @Override
    public void process(Object[] objects) throws HiveException {
        //获取输入数据
        String input = objects[0].toString();

        if(StringUtils.isBlank(input)){
            return ;
        }else{
            try {
                JSONArray ja = new JSONArray(input);
                if(ja==null){
                    return;
                }
                for(int i = 0;i<ja.length();i++){
                    String[] results = new String[2];
                    try {
                        results[0] = ja.getJSONObject(i).getString("en");
                        results[1] = ja.getString(i);
                    } catch (JSONException e) {
                        e.printStackTrace();
                        continue;
                    }
                    forward(results);
                }

            } catch (JSONException e) {
                e.printStackTrace();

            }

        }
    }

    @Override
    public void close() throws HiveException {

    }
}

打包好去hive导入jar包建立函数以编写导入代码

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set hive.exec.dynamic.partition.mode=nonstrict;
 
insert overwrite table dwd_base_event_log
PARTITION (dt='2019-02-10')
select
mid_id,
user_id,
version_code,
version_name,
lang,
source,
os,
area,
model,
brand,
sdk_version,
gmail,
height_width,
app_time,
network,
lng,
lat,
event_name,
event_json,
server_time
from
(
select
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[0]   as mid_id,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[1]   as user_id,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[2]   as version_code,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[3]   as version_name,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[4]   as lang,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[5]   as source,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[6]   as os,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[7]   as area,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[8]   as model,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[9]   as brand,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[10]   as sdk_version,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[11]  as gmail,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[12]  as height_width,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[13]  as app_time,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[14]  as network,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[15]  as lng,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[16]  as lat,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[17]  as ops,
split(base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la'),'\t')[18]  as server_time
from ods_event_log where dt='2019-02-10'  and base_analizer(line,'mid,uid,vc,vn,l,sr,os,ar,md,ba,sv,g,hw,t,nw,ln,la')<>''
) sdk_log lateral view flat_analizer(ops) tmp_k as event_name, event_json;

至此即为这个阶段最关键重要的步骤。
其他枯燥的建表插入环节就不再赘述（十张表，不断地从dwd_base_event_log换字段创建插入，属实枯燥，不过真的很佩服能设计出10张表完成数仓基本功能的数据库设计师）
这里附上一键插入shell脚本，表的话该创害得自己去按照需求创

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dwd_event_log.sh
#!/bin/bash

# 定义变量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive

# 如果是输入的日期按照取输入日期；如果没输入日期取当前时间的前一天
if [ -n "$1" ] ;then
	do_date=$1
else 
	do_date=`date -d "-1 day" +%F`  
fi 

sql="
set hive.exec.dynamic.partition.mode=nonstrict;

insert overwrite table "$APP".dwd_display_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.action') action,
	get_json_object(event_json,'$.kv.goodsid') goodsid,
	get_json_object(event_json,'$.kv.place') place,
	get_json_object(event_json,'$.kv.extend1') extend1,
	get_json_object(event_json,'$.kv.category') category,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='display';


insert overwrite table "$APP".dwd_newsdetail_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.entry') entry,
	get_json_object(event_json,'$.kv.action') action,
	get_json_object(event_json,'$.kv.goodsid') goodsid,
	get_json_object(event_json,'$.kv.showtype') showtype,
	get_json_object(event_json,'$.kv.news_staytime') news_staytime,
	get_json_object(event_json,'$.kv.loading_time') loading_time,
	get_json_object(event_json,'$.kv.type1') type1,
	get_json_object(event_json,'$.kv.category') category,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='newsdetail';


insert overwrite table "$APP".dwd_loading_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.action') action,
	get_json_object(event_json,'$.kv.loading_time') loading_time,
	get_json_object(event_json,'$.kv.loading_way') loading_way,
	get_json_object(event_json,'$.kv.extend1') extend1,
	get_json_object(event_json,'$.kv.extend2') extend2,
	get_json_object(event_json,'$.kv.type') type,
	get_json_object(event_json,'$.kv.type1') type1,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='loading';


insert overwrite table "$APP".dwd_ad_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.entry') entry,
	get_json_object(event_json,'$.kv.action') action,
	get_json_object(event_json,'$.kv.content') content,
	get_json_object(event_json,'$.kv.detail') detail,
	get_json_object(event_json,'$.kv.source') ad_source,
	get_json_object(event_json,'$.kv.behavior') behavior,
	get_json_object(event_json,'$.kv.newstype') newstype,
	get_json_object(event_json,'$.kv.show_style') show_style,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='ad';


insert overwrite table "$APP".dwd_notification_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.action') action,
	get_json_object(event_json,'$.kv.noti_type') noti_type,
	get_json_object(event_json,'$.kv.ap_time') ap_time,
	get_json_object(event_json,'$.kv.content') content,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='notification';


insert overwrite table "$APP".dwd_active_foreground_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
get_json_object(event_json,'$.kv.push_id') push_id,
get_json_object(event_json,'$.kv.access') access,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='active_foreground';


insert overwrite table "$APP".dwd_active_background_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.active_source') active_source,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='active_background';


insert overwrite table "$APP".dwd_comment_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.comment_id') comment_id,
	get_json_object(event_json,'$.kv.userid') userid,
	get_json_object(event_json,'$.kv.p_comment_id') p_comment_id,
	get_json_object(event_json,'$.kv.content') content,
	get_json_object(event_json,'$.kv.addtime') addtime,
	get_json_object(event_json,'$.kv.other_id') other_id,
	get_json_object(event_json,'$.kv.praise_count') praise_count,
	get_json_object(event_json,'$.kv.reply_count') reply_count,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='comment';


insert overwrite table "$APP".dwd_favorites_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.id') id,
	get_json_object(event_json,'$.kv.course_id') course_id,
	get_json_object(event_json,'$.kv.userid') userid,
	get_json_object(event_json,'$.kv.add_time') add_time,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='favorites';


insert overwrite table "$APP".dwd_praise_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.id') id,
	get_json_object(event_json,'$.kv.userid') userid,
	get_json_object(event_json,'$.kv.target_id') target_id,
	get_json_object(event_json,'$.kv.type') type,
	get_json_object(event_json,'$.kv.add_time') add_time,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='praise';


insert overwrite table "$APP".dwd_error_log
PARTITION (dt='$do_date')
select 
	mid_id,
	user_id,
	version_code,
	version_name,
	lang,
	source,
	os,
	area,
	model,
	brand,
	sdk_version,
	gmail,
	height_width,
	app_time,
	network,
	lng,
	lat,
	get_json_object(event_json,'$.kv.errorBrief') errorBrief,
	get_json_object(event_json,'$.kv.errorDetail') errorDetail,
	server_time
from "$APP".dwd_base_event_log 
where dt='$do_date' and event_name='error';
"

$hive -e "$sql"

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本文标题:【数仓项目】百尺竿头,更进一步-dwd层构建

文章作者:Sumiyax

发布时间:2020年03月19日 - 23时38分

最后更新:2020年03月20日 - 00时13分

原始链接:http://yoursite.com/2020/03/19/【数仓项目】百尺竿头-更进一步-dwd层构建/

许可协议: "署名-非商用-相同方式共享 3.0" 转载请保留原文链接及作者。

文章目录
  1. 1. 难点：event部分：
,