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: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 '$Cleaned_Log' USING PigStorage(',') --读取日志文件
AS (ad_network_id:chararray,
xxx_ad_id:chararray,
guid:chararray,
id:chararray,
create_time:chararray,
action_time:chararray,
log_type:chararray,
ad_id:chararray,
positioning_method:chararray,
location_accuracy:chararray,
lat:chararray,
lon:chararray,
cell_id:chararray,
lac:chararray,
mcc:chararray,
mnc:chararray,
ip:chararray,
connection_type:chararray,
Android_id:chararray,
android_advertising_id:chararray,
openudid:chararray,
mac_address:chararray,
uid:chararray,
density:chararray,
screen_height:chararray,
screen_width:chararray,
user_agent:chararray,
app_id:chararray,
app_category_id:chararray,
device_model_id:chararray,
carrier_id:chararray,
os_id:chararray,
device_type:chararray,
os_version:chararray,
country_region_id:chararray,
province_region_id:chararray,
city_region_id:chararray,
ip_lat:chararray,
ip_lon:chararray,
quadkey:chararray);
--loading metadata/ad(adId,campaignId)
metadata_ad = LOAD '$AD_Data' USING PigStorage(',') AS (adId:chararray, campaignId:chararray);
--loading metadata/campaignæ•°æ®(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;