hive行轉列

selectt1.base,concat_ws('|', collect_set(t1.name)) namefrom(selectname,concat(constellation, "," , blood_type) basefromperson_info) t1group byt1.base;

hive列轉行

select movie, category_name from movie_info lateral view explode(category) table_tmp as category_name;

reflect調用Java自帶函數

select reflect("java.lang.Math","max",col1,col2) from test_udf; select reflect(class_name,method_name,col1,col2) from test_udf2; select reflect("org.apache.commons.lang.math.NumberUtils","isNumber","123")

窗口函數

select user_id, user_type, sales, --分組內所有行 sum(sales) over(partition by user_type) AS sales_1 , sum(sales) over(order by user_type) AS sales_2 , --默認為從起點到當前行，如果sales相同，累加結果相同 sum(sales) over(partition by user_type order by sales asc) AS sales_3, --從起點到當前行，結果與sales_3不同。 根據排序先后不同，可能結果累加不同 sum(sales) over(partition by user_type order by sales asc rows between unbounded preceding and current row) AS sales_4, --當前行+往前3行 sum(sales) over(partition by user_type order by sales asc rows between 3 preceding and current row) AS sales_5, --當前行+往前3行+往后1行 sum(sales) over(partition by user_type order by sales asc rows between 3 preceding and 1 following) AS sales_6, --當前行+往后所有行 sum(sales) over(partition by user_type order by sales asc rows between current row and unbounded following) AS sales_7 from order_detail order by user_type,sales,user_id;

分析函數

select user_id,user_type,sales,RANK() over (partition by user_type order by sales desc) as r,ROW_NUMBER() over (partition by user_type order by sales desc) as rn,DENSE_RANK() over (partition by user_type order by sales desc) as dr fromorder_detail;

cube聚合

selectuser_type,sales,count(user_id) as pv,GROUPING__ID from order_detail group by user_type,sales WITH CUBE ORDER BY GROUPING__ID;

總結

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