join

How to update one table from another table based on some priority that depends on where clause?

為{幸葍}努か 提交于 2020-04-17 22:04:53
问题 I have table A with product_id,cost,year,quarter,... etc columns. I have another table B with product_id,base_cost,current_year,p_year,p_quarter,p_order columns. I want to write an update query to update A from B. My conditions are - WHERE A.product_id=B.product_id and A.year=B.current_year and (A.year=B.p_year and A.quarter>B.p_quarter) or A.year>B.p_year and A.cost=0; But the problem is, with these conditions if i have more than one rows in B then i only want to update from the row of B

查询pg一张表下有哪些索引

你说的曾经没有我的故事 提交于 2020-04-07 21:07:46
<!--查询一张表下有哪些索引,如查询report.common_count下所有索引--> select A.SCHEMANAME, A.TABLENAME, A.INDEXNAME, A.TABLESPACE, A.INDEXDEF, B.AMNAME, C.INDEXRELID, C.INDNATTS, C.INDISUNIQUE, C.INDISPRIMARY, C.INDISCLUSTERED, D.DESCRIPTION from PG_AM B left join PG_CLASS F on B.OID = F.RELAM left join PG_STAT_ALL_INDEXES E on F.OID = E.INDEXRELID left join PG_INDEX C on E.INDEXRELID = C.INDEXRELID left outer join PG_DESCRIPTION D on C.INDEXRELID = D.OBJOID, PG_INDEXES A where A.SCHEMANAME = E.SCHEMANAME and A.TABLENAME = E.RELNAME and A.INDEXNAME = E.INDEXRELNAME and E.SCHEMANAME = ' schema_name ' and E.RELNAME =

hive 的判断条件(if、coalesce、case)

穿精又带淫゛_ 提交于 2020-04-07 17:13:37
CONDITIONAL FUNCTIONS IN HIVE Hive supports three types of conditional functions. These functions are listed below: IF( Test Condition, True Value, False Value ) The IF condition evaluates the “Test Condition” and if the “Test Condition” is true, then it returns the “True Value”. Otherwise, it returns the False Value. Example: IF(1=1, 'working', 'not working') returns 'working' COALESCE( value1,value2,... ) The COALESCE function returns the fist not NULL value from the list of values. If all the values in the list are NULL, then it returns NULL. Example: COALESCE(NULL,NULL,5,NULL,4) returns 5

【原创】大叔问题定位分享(11)Spark中对大表子查询加limit为什么会报Broadcast超时错误

对着背影说爱祢 提交于 2020-04-06 12:44:54
当两个表需要join时,如果一个是大表,一个是小表,正常的map-reduce流程需要shuffle,这会导致大表数据在节点间网络传输,常见的优化方式是将小表读到内存中并广播到大表处理,避免shuffle+reduce; 在hive中叫mapjoin(map-side join),配置为 hive.auto.convert.join 在spark中叫BroadcastHashJoin (broadcast hash join) Spark SQL uses broadcast join (aka broadcast hash join) instead of hash join to optimize join queries when the size of one side data is below spark.sql.autoBroadcastJoinThreshold . Broadcast join can be very efficient for joins between a large table (fact) with relatively small tables (dimensions) that could then be used to perform a star-schema join. It can avoid sending all data

js对象、数组转换字符串

佐手、 提交于 2020-04-06 08:10:20
对象转换成字符串需要使用toString()方法。 1 var a = function(){ 2 console.log(111); 3 }; 4 var b = a.toString(); 5 console.log(a); 函数式的function 6 console.log(b); 字符串function 7 console.log(typeof a); >>function 8 console.log(typeof b); >>string 数组转换字符串 1.0 1 var a = [1,2,3]; 2 var b = a.toString(); 3 console.log(a); >>[1,2,3] 4 console.log(b); >>"1,2,3" 当我们进行与原始值比较的时候,它们会自动调用toString方法。(+,-,!=,==都会进行转换。) 数组转换字符串 2.0 1 // var a = [1,2,3]; 2 // console.log(a.join()); >>1,2,3 toString()与join()的比较 1 // var a = [1,2,3]; 2 // console.log(a.join()); >>1,2,3 3 // console.log(a.toString()); >>1,2,3 4 // console.log(a

Which one will perform better, broadcast variable or broadcast join?

懵懂的女人 提交于 2020-04-03 10:44:52
问题 I am using Spark 2.4.1 with Java 8 in my project. I have a scenario where I need to look-up another table/dataset which has two fields i.e. country-name and country-code. Another stream-data will have country-code column in it, I need to map respective country-name in the target/result dataframe. As far as I know, we can use join to achieve the above, using broadcast variable and joining. So from performance point of view which one is better here? What is the spark standard to handle this

Which one will perform better, broadcast variable or broadcast join?

五迷三道 提交于 2020-04-03 10:43:50
问题 I am using Spark 2.4.1 with Java 8 in my project. I have a scenario where I need to look-up another table/dataset which has two fields i.e. country-name and country-code. Another stream-data will have country-code column in it, I need to map respective country-name in the target/result dataframe. As far as I know, we can use join to achieve the above, using broadcast variable and joining. So from performance point of view which one is better here? What is the spark standard to handle this

laravel left join携带多个条件的写法

本秂侑毒 提交于 2020-03-26 14:58:09
3 月,跳不动了?>>> 在laravel中使用leftJoin添加多个条件时,如select a.* from a left join b on a.id = b.pid and b.status = 1这种类似sql,发现框架自身封装的leftJoin不支持多个参数传递(当然可用写原生sql),laravel框架自身封装的leftJoin方法如下: public function leftJoin($table, $first, $operator = null, $second = null) { return $this->join($table, $first, $operator, $second, 'left'); } 浏览下 \vendor\laravel\framework\src\Illuminate\Database\Query\Builder.php文件,发现join方法可用实现自己想要的left join携带多参数。laravel自身的join方法如下: public function join($table, $one, $operator = null, $two = null, $type = 'inner', $where = false) { // If the first "column" of the join is really a

laravel join 多条件

纵然是瞬间 提交于 2020-03-26 14:54:37
3 月,跳不动了?>>> -> leftjoin ( 'bill_detail as bl_refund' , function ( $joins ) { $joins -> on ( 'bl_refund.bill_id' , '=' , 'bl.bill_id' ) ; $joins -> where ( 'bl_refund.settle_type' , '=' , 7 ) ; }) 来源: oschina 链接: https://my.oschina.net/guozhouyuan/blog/3211854