• pig简单的代码实例:报表统计行业中的点击和曝光量


    注意:pig中用run或者exec 运行脚本。除了cd和ls,其他命令不用。在本代码中用rm和mv命令做例子,容易出错。

    另外,pig只有在store或dump时候才会真正加载数据,否则,只是加载代码,不具体操作数据。所以在rm操作时必须注意该文件是否已经生成。如果rm的文件为生成,可以第三文件,进行mv改名操作


    SET job.name 'test_age_reporth_istorical';-- 定义任务名字,在http://172.XX.XX.XX:50030/jobtracker.jsp中查看任务状态,失败成功。

    SET job.priority HIGH;--优先级


    --注册jar包,用于读取sequence file和输出分析结果文件
    REGISTER piggybank.jar;
    DEFINE SequenceFileLoader org.apache.pig.piggybank.storage.SequenceFileLoader(); --读取二进制文件,函数名定义


    %default Cleaned_Log /user/C/data/XXX/cleaned/$date/*/part* --$date是外部传入参数


    %default AD_Data /user/XXX/data/xxx/metadata/ad/part*
    %default Campaign_Data /user/xxx/data/xxx/metadata/campaign/part*
    %default Social_Data /user/xxx/data/report/socialdata/part*


    --所有的输出文件路径:
    %default Industry_Path $file_path/report/historical/age/$year/industry
    %default Industry_SUM $file_path/report/historical/age/$year/industry_sum
    %default Industry_TMP $file_path/report/historical/age/$year/industry_tmp


    %default Industry_Brand_Path $file_path/report/historical/age/$year/industry_brand
    %default Industry_Brand_SUM $file_path/report/historical/age/$year/industry_brand_sum
    %default Industry_Brand_TMP $file_path/report/historical/age/$year/industry_brand_tmp


    %default ALL_Path $file_path/report/historical/age/$year/all
    %default ALL_SUM $file_path/report/historical/age/$year/all_sum
    %default ALL_TMP $file_path/report/historical/age/$year/all_tmp


    %default output_path /user/xxx/tmp/result




    origin_cleaned_data = LOAD '$Cleaned_Log' USING PigStorage(',') --读取日志文件
    AS (ad_network_id:chararray,
        xxx_ad_id:chararray,
        guid:chararray,
        id:chararray,
        create_time:chararray,
        action_time:chararray,
        log_type:chararray, 
        ad_id:chararray,
        positioning_method:chararray,
        location_accuracy:chararray,
        lat:chararray, 
        lon:chararray,
        cell_id:chararray,
        lac:chararray,
        mcc:chararray,
        mnc:chararray,
        ip:chararray,
        connection_type:chararray,
        android_id:chararray,
        android_advertising_id:chararray,
        openudid:chararray,
        mac_address:chararray,
        uid:chararray,
        density:chararray,
        screen_height:chararray,
        screen_chararray,
        user_agent:chararray,
        app_id:chararray,
        app_category_id:chararray,
        device_model_id:chararray,
        carrier_id:chararray,
        os_id:chararray,
        device_type:chararray,
        os_version:chararray,
        country_region_id:chararray,
        province_region_id:chararray,
        city_region_id:chararray,
        ip_lat:chararray,
        ip_lon:chararray,
        quadkey:chararray);


    --loading metadata/ad(adId,campaignId) 
    metadata_ad = LOAD '$AD_Data' USING PigStorage(',') AS (adId:chararray, campaignId:chararray);


    --loading metadata/campaign数据(campaignId, industryId, brandId)
    metadata_campaign = LOAD '$Campaign_Data' USING PigStorage(',') AS (campaignId:chararray, industryId:chararray, brandId:chararray);


    --ad and campaign for inner join
    joinAdCampaignByCampaignId = JOIN metadata_ad BY campaignId,metadata_campaign BY campaignId;--(adId,campaignId,campaignId,industryId,brandId)
    --filtering out redundant column of joinAdCampaignByCampaignId
    joined_ad_campaign_data = FOREACH joinAdCampaignByCampaignId GENERATE $0 AS adId,$3 AS industryId,$4 AS brandId; --(adId,industryId,brandId)


    --extract column for analyzing
    origin_historical_age = FOREACH origin_cleaned_data GENERATE xxx_ad_id,guid,log_type;--(xxx_ad_id,guid,log_type)
    --distinct
    distinct_origin_historical_age = DISTINCT origin_historical_age;--(xxx_ad_id,guid,log_type)


    --loading metadata_region(guid_social, sex, age, income, edu, hobby)
    metadata_social = LOAD '$Social_Data' USING PigStorage(',') AS (guid_social:chararray, sex:chararray, age:chararray, income:chararray, edu:chararray, hobby:chararray);
    --extract needed column in metadata_social
    social_age = FOREACH metadata_social GENERATE guid_social,age;


    --join socialData(metadata_social) and logData(distinct_origin_historical_age):
    joinedByGUID = JOIN social_age BY guid_social, distinct_origin_historical_age BY guid;
    --(guid_social, age; xxx_ad_id,guid,log_type)




    --generating analyzing age data
    joined_orgin_age_data = FOREACH joinedByGUID GENERATE xxx_ad_id,guid,log_type,age;
    joinedByAdId = JOIN joined_ad_campaign_data BY adId, joined_orgin_age_data BY xxx_ad_id; --(adId,industryId,brandId,xxx_ad_id,guid,log_type,age)
    --filtering
    all_current_data = FOREACH joinedByAdId GENERATE guid,log_type,industryId,brandId,age; --(guid,log_type,industryId,brandId,age)


    --for industry analyzing
    industry_current_data = FOREACH all_current_data GENERATE industryId,guid,age,log_type;  --(industryId,guid,age,log_type)


    --load all in the path "industry"
    industry_existed_Data = LOAD '$Industry_Path' USING PigStorage(',') AS (industryId:chararray,guid:chararray,age:chararray,log_type:chararray);


    --merge with history data 
    union_Industry = UNION industry_existed_Data, industry_current_data;
    distict_union_industry = DISTINCT union_Industry;
    group_industry = GROUP distict_union_industry BY ($2,$0,$3);
    count_guid_for_industry = FOREACH group_industry GENERATE FLATTEN(group),COUNT($1.$1);


    rm $Industry_SUM;
    STORE count_guid_for_industry INTO '$Industry_SUM' USING PigStorage(',');


    --storing union industry data(current and history)
    STORE distict_union_industry INTO '$Industry_TMP' USING PigStorage(',');
    rm $Industry_Path
    mv $Industry_TMP $Industry_Path


    --counting guid for industry and brand 
    industry_brand_current = FOREACH all_current_data GENERATE age,industryId,brandId,log_type,guid;
    --(age,industryId,brandId,log_type,guid)


    --load history data of industry_brand
    industry_brand_history = LOAD '$Industry_Brand_Path' USING PigStorage(',') AS(age:chararray, industryId:chararray, brandId:chararray, log_type:chararray, guid:chararray);


    --union all data of industry_brand
    union_industry_brand = UNION industry_brand_current,industry_brand_history;
    unique_industry_brand = DISTINCT union_industry_brand;
    --(age,industryId,brandId,log_type,guid)


    --counting users' number for industry and brand
    group_industry_brand = GROUP unique_industry_brand BY ($0,$1,$2,$3);
    count_guid_for_industry_brand = FOREACH group_industry_brand GENERATE FLATTEN(group),COUNT($1.$4);


    rm $Industry_Brand_SUM;
    STORE count_guid_for_industry_brand INTO '$Industry_Brand_SUM' USING PigStorage(',');


    STORE unique_industry_brand INTO '$Industry_Brand_TMP' USING PigStorage(',');
    rm $Industry_Brand_Path;
    mv $Industry_Brand_TMP $Industry_Brand_Path


    --counting user number for age and logtype
    current_data = FOREACH all_current_data GENERATE age,log_type,guid;--(age,log_type,guid)


    --load history data of age and logtype
    history_data = LOAD '$ALL_Path' USING PigStorage(',') AS(age:chararray,log_type:chararray,guid:chararray);


    --union current and history data
    union_all_data = UNION history_data, current_data;
    unique_all_data = DISTINCT union_all_data;


    --count users' number
    group_all_data = GROUP unique_all_data BY ($0,$1);
    count_guid_for_age_logtype = FOREACH group_all_data GENERATE FLATTEN(group),COUNT($1.$2);


    rm $ALL_SUM;
    STORE count_guid_for_age_logtype INTO '$ALL_SUM' USING PigStorage(',');


    STORE unique_all_data INTO '$ALL_TMP' USING PigStorage(',');
    rm $ALL_Path
    mv $ALL_TMP $ALL_Path

  • 相关阅读:
    dubbo源码解析-spi(3)
    dubbo源码解析-spi(二)
    dubbo源码解析-spi(一)
    java-nio之zero copy深入分析
    Java SPI(Service Provider Interface)简介
    分析 Java heap dump工具之IBM HeapAnalyzer
    深入理解分布式事务
    NIO中的heap Buffer和direct Buffer区别
    Guava之Iterables使用示例
    Android开发中常见的设计模式 MD
  • 原文地址:https://www.cnblogs.com/cl1024cl/p/6205417.html
Copyright © 2020-2023  润新知