loongshawn的博客

如何提前JSON属性针对json数组提取待处理数据[{"id": "123456789", "orgID": "group", "empName": "张三", "empID": "93002", "orgNamePath": "数据中心/高德地图/阿里巴巴"}]SQL写法SELECTget_json_object( regexp_replace( regexp_replace(field, '\\[', ''), '\\]', '' ) -- 提取json对象

异常1、常见异常StatementCallback; uncategorized SQLException for SQL [select * from `xxx` where time= '20190404']; SQL state [HY000]; error code [0]; File 'hdfs://xxx/xxx/time=20190404/xxxxxxxxxx' has an incompatible Parquet schema for column 'xxx.xxx'. Column

场景分组后的数据多行聚合成一行序号idclasstag11AAf21BBf31CCf41DDf51EEf62QQf72WWf82MMf期望序号idclass11AA,BB,CC22QQ,WW,MM实现两步走先分组再拼接with temp as ( select id as id, class as class

需求来源impala查询问题描述Impala查询表报如下异常nested exception is java.sql.SQLException: File 'hdfs://nameservice/loongshawn/d/table/p_date=2018-01/part-xxxxxxxxxxxx' has an incompatible Parquet schema for column 'v.table.fileed'. Column type: DOUBLE, Parquet schema:

绿码是如何变黄、变红，数据计算赋能

需求来源对列值分组，并按一定顺序排序，最后多行合并一行，合并值左到右逆序排列。问题描述select t.id, concat_ws(',', collect_set(t.class))from temp tgroup by t.id原始temp数据idclassloongshaw1loongshaw2loongshaw3loongshaw4期望值idclassloongshaw1,2,3,4.

异常回顾2019-01-01 11:24:32,035 WARN org.apache.spark.scheduler.TaskSetManager: Lost task xx.0 in stage x.0 (xxx 12, xxx, executor 3): org.apache.spark.SparkException: Task failed while writing rows at org.apache.spark.sql.execution.datasources.FileFormatWri

impala/spark常见的命令汇总 待完善