pig分析脚本

课程内容：各种k8s部署方式。包括minikube部署，kubeadm部署，kubeasz部署，rancher部署，k3s部署。包括开发测试环境部署k8s，和生产环境部署k8s。

腾讯课堂连接地址https://ke.qq.com/course/478827?taid=4373109931462251&tuin=ba64518

腾讯课堂连接地址https://ke.qq.com/course/484107?tuin=ba64518

介绍主要的k8s资源的使用配置和命令。包括configmap，pod，service，replicaset，namespace，deployment，daemonset，ingress，pv，pvc，sc，role，rolebinding，clusterrole，clusterrolebinding，secret，serviceaccount，statefulset，job，cronjob，podDisruptionbudget，podSecurityPolicy,networkPolicy,resourceQuota，limitrange，endpoint，event，conponentstatus，node，apiservice，controllerRevision等。

第三个视频发布：https://edu.csdn.net/course/detail/27574

详细介绍helm命令，学习helm chart语法，编写helm chart。深入分析各项目源码，学习编写helm插件
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--读取数据
data = LOAD '/user/mapred/PigData.txt' USING PigStorage('|') AS ( imsi:chararray,time:chararray,loc:chararray);


--转换格式
REGISTER /home/mapred/software/hadoops/pig/pig-0.11.1/contrib/piggybank/java/piggybank.jar;
REGISTER /home/mapred/practise/joda-time-2.0.jar;


DEFINE CustomFormatToISO org.apache.pig.piggybank.evaluation.datetime.convert.CustomFormatToISO();


toISO = FOREACH data GENERATE imsi, CustomFormatToISO( SUBSTRING(time,0,13),'YYYY-MM-dd HH') AS time:chararray,loc;


--数据分组
grp = GROUP toISO BY imsi;


--连续获取数据
REGISTER /home/mapred/practise/datafu-1.2.0.jar
DEFINE MarkovPairs datafu.pig.stats.MarkovPairs();


pairs = FOREACH grp
{
sorted = ORDER toISO BY time;
pair = MarkovPairs(sorted);
GENERATE FLATTEN(pair) AS (data:tuple(imsi,time,loc),next:tuple(imsi,time,loc) );
}


--展开数据
prj = FOREACH pairs GENERATE data.imsi AS imsi,data.time AS time,next.time AS next_time,data.loc AS loc,next.loc AS next_loc;




DEFINE ISODaysBetween org.apache.pig.piggybank.evaluation.datetime.diff.ISODaysBetween();


flt = FILTER prj BY ISODaysBetween(next_time, time) == 0L;




--计算每一个位置的总数


total_count = FOREACH (GROUP flt BY loc) GENERATE group AS loc,COUNT(flt) AS total;


--计算每一对位置的数目
pairs_count = FOREACH (GROUP flt by (loc,next_loc) ) GENERATE FLATTEN(group) AS (loc,next_loc),COUNT(flt) AS cnt;




jnd = JOIN pairs_count BY loc,total_count BY loc USING 'replicated';


prob = FOREACH jnd GENERATE pairs_count::loc AS loc, pairs_count::next_loc AS next_loc,(double)cnt/(double)total AS probability;


top3 = FOREACH (GROUP prob BY loc)
{
sorted = ORDER prob BY probability DESC;
top = LIMIT sorted 3;
GENERATE FLATTEN(top);
};


STORE top3 INTO 'output';


cat output;