spark sql join

Original address: Spark SQL joins implementation of Spark SQL joinShangang 2017-07-19 217 Tags: spark, database Join as an important syntax feature in SQL, almost all of the slightly

Products A table of changes in the price of goods, orders, records each purchase of goods and datesMatch orders and products based on a non-equivalent join in Spark SQL, counting the prices of the items in each orderSlow-changing commodity price listWangzai milk, there was a price change.scala> val products = sc.parallelize(Array( | ("旺仔牛奶", "2017-01-01", "

Tags: LVS and List serve log enter war field dataWhen you use join for two dataframe in Spark SQL, the value of the field as a connection contains a null value . Because the meaning of the null representation is unknown, neither does it know that the comparison of null values in SQL with any other value (even if null)

outer joinrows =Sqlctx.sql ("Select Table1.name, Table1.title, table2.fraction from table1 to outer join table2 on table1.name = Table2.name"). Collect () printrows (rows)#Right outer joinrows =Sqlctx.sql ("Select Table1.name, Table1.title, table2.fraction from table1 right outer join table2 on table1.name = Table2.name"). Collect ()Print "============================================="printrows (rows)#Full

the same as that in the previous example! 4: Inner join or join; It is the record that the returned field ID exists in both the table votemaster and voter.5: Cross join (full join) with no where Condition A cross join without a where clause will generate the Cartesian produ

without the where ConditionA cross join without a where clause will generate the Cartesian product of the table involved in the join. The number of rows in the first table multiplied by the number of rows in the second table is equal to the size of the Cartesian result set. (Table 1 and Table 2 generate 6*3 = 18 Records)Equivalent to select VM. ID, VM. votetitle, vt. IP from votemaster as Vm, voter as vt

Spark cultivation (advanced)-Spark beginners: Section 13th Spark Streaming-Spark SQL, DataFrame, and Spark StreamingMain Content: Spark SQL,

Label:Main content Spark SQL, Dataframe, and spark streaming 1. Spark SQL, dataframe and spark streamingSOURCE Direct reference: https://github.com/apache/spark/blob/maste

SQL join is used to query data from these tables based on the relationship between the columns in two or more tables.Join and KeySometimes in order to get the complete result, we need to get the results from two or more tables. We need to execute the join.Tables in the database can be linked by keys. The primary key (Primary key) is a column, and the value of each row in the column is unique. In the table,

following commands in the query Analyzer: 1. External Connection1. Concept: including left Outer Join, right Outer Join or complete external join 2. Left join: left join or left Outer Join(1) The result set of the left Outer

Original link: http://www.powerxing.com/sql-join/In general, the use/difference of four joins can be described as: The LEFT join returns all records from the table (shop), even if there are no matching rows in the right table (Sale_detail). Right outer join, returns all records in the right table, even if

The following is a 137-row SQL statement. If you understand this, I want to know about left join and inner join. (My personal opinion only) The following is a piece of code: Select num1, num2, num3, num4, num5, num6, num7, num8, num9, num10, area. areacode, area. areaname, num11 From(Select area_code areacode, area_name areaname, Fa. grade_path grade, Fa. IDFrom

Joins are divided into:INNER JOIN???????????????????????? [INNER JOIN]Outer JOIN???????? (left outer join, right outer join)???????? [Left Join/left outer joins, right join/right outer

right table, regardless of whether the table on the left has matching data: Select S.name,m.mark from student s right join Mark M on S.id=m.studentid Iv. fully connected-full join: Using the format as above has been explained above Remove the data from the left and right two tables, whether or not they match: Select S.name,m.mark from student s full join Mark M

two results were met, and the results were as follows: Second, left join connect-left join: Left join is to select all the tuples from the left table: Select S.name,m.mark from student s left join Mark M on S.id=m.studentid The above statement is the left side of the table, that is, the tuple in the student table is

-right join: The right connection is to remove all data from the right table, regardless of whether the table on the left has matching data: Select S.name,m.mark from student s right join Mark M on S.id=m.studentid The above statement takes all the data from the Mark score table, regardless of whether there is a data match in the student table, as shown in: Iv. fully connected-full

: The right connection is to remove all data from the right table, regardless of whether the table on the left has matching data: Select S.name,m.mark from student s right join Mark M on S.id=m.studentid The above statement takes all the data from the Mark score table, regardless of whether there is a data match in the student table, as shown in: Iv. fully connected-full join: Remove the data from the lef

Cross Jointable2Select * fromTable1,table2--The following three statements have the same effectSelect * fromTable1 A,table2 bwhereb.ID=a.idSelect * fromTable1 A Cross JoinTable2 bwhereb.ID=a.idSelect * fromTable1 AInner JoinTable2 b onb.ID=a.ID2 Cross Apply,outer apply(Cross Apply,outer apply is new in SQL Server 2005)There is a cross join in SQL Server 2000

SQL table join query (inner join, full join, left join, right join) Prerequisites: Assume that there are two tables, one is the student table and the other is the student renewal table. Table data includes: I. inne

, regardless of whether the table on the left has matching data: Select S.name,m.mark from student s right join Mark M on S.id=m.studentid The above statement takes all the data from the Mark score table, regardless of whether there is a data match in the student table, as shown in: Iv. fully connected-full join: Remove the data from the left and right two tables, whether or not they match: Select S.name,