- Article
- 10 minutes to read
Merge the rows of two tables to form a new table by matching values of the specified columns from each table.
Table1 | join (Table2) on CommonColumn, $left.Col1 == $right.Col2Syntax
LeftTable | join [JoinParameters] ( RightTable ) on Attributes
Arguments
LeftTable: The left table or tabular expression, sometimes called outer table, whose rows are to be merged. Denoted as
$left.RightTable: The right table or tabular expression, sometimes called inner table, whose rows are to be merged. Denoted as
$right.Attributes: One or more comma-separated rules that describe how rows fromLeftTable are matched to rows from RightTable. Multiple rules are evaluated using the
andlogical operator.A rule can be one of:
Rule kind Syntax Predicate Equality by name ColumnName whereLeftTable.ColumnName==RightTable.ColumnNameEquality by value $left.LeftColumn==$right.RightColumnwhere$left.LeftColumn==$right.RightColumnNote
For 'equality by value', the column names must be qualified with the applicable owner table denoted by
$leftand$rightnotations.JoinParameters: Zero or more space-separated parameters in the form of Name
=Value that control the behavior of the row-match operation and execution plan. The following parameters are supported:Parameters name Values Description kindJoin flavors See Join Flavors hint.remoteauto,left,local,rightSee Cross-Cluster Join hint.strategy=broadcastSpecifies the way to share the query load on cluster nodes. See broadcast join hint.shufflekey=<key>The shufflekeyquery shares the query load on cluster nodes, using a key to partition data.See shuffle query hint.strategy=shuffleThe shufflestrategy query shares the query load on cluster nodes, where each node will process one partition of the data.See shuffle query Name Values Description kindJoin flavors See Join Flavors hint.remoteauto,left,local,righthint.strategy=broadcastSpecifies the way to share the query load on cluster nodes. See broadcast join hint.shufflekey=<key>The shufflekeyquery shares the query load on cluster nodes, using a key to partition data.See shuffle query hint.strategy=shuffleThe shufflestrategy query shares the query load on cluster nodes, where each node will process one partition of the data.See shuffle query
Warning
If kind isn't specified, the default join flavor is innerunique. This is different than some other analytics products that have inner as the default flavor. See join-flavors to understand the differences and make sure the query yields the intended results.
Returns
The output schema depends on the join flavor:
| Join flavor | Output schema |
|---|---|
kind=leftanti, kind=leftsemi | The result table contains columns from the left side only. |
kind=rightanti, kind=rightsemi | The result table contains columns from the right side only. |
kind=innerunique, kind=inner, kind=leftouter, kind=rightouter, kind=fullouter | A column for every column in each of the two tables, including the matching keys. The columns of the right side will be automatically renamed if there are name clashes. |
Output records depend on the join flavor:
Note
If there are several rows with the same values for those fields, you'll get rows for all the combinations.A match is a row selected from one table that has the same value for all the on fields as a row in the other table.
| Join flavor | Output records |
|---|---|
kind=leftanti, kind=leftantisemi | Returns all the records from the left side that don't have matches from the right |
kind=rightanti, kind=rightantisemi | Returns all the records from the right side that don't have matches from the left. |
kind unspecified, kind=innerunique | Only one row from the left side is matched for each value of the on key. The output contains a row for each match of this row with rows from the right. |
kind=leftsemi | Returns all the records from the left side that have matches from the right. |
kind=rightsemi | Returns all the records from the right side that have matches from the left. |
kind=inner | Returns all matching records from left and right sides. |
kind=fullouter | Returns all the records for all the records from the left and right sides. Unmatched cells contain nulls. |
kind=leftouter | Returns all the records from the left side and only matching records from the right side. |
kind=rightouter | Returns all the records from the right side and only matching records from the left side. |
Tip
For best performance, if one table is always smaller than the other, use it as the left (piped) side of the join.
Example
Get extended activities from a login that some entries mark as the start and end of an activity.
let Events = MyLogTable | where type=="Event" ;Events| where Name == "Start"| project Name, City, ActivityId, StartTime=timestamp| join (Events | where Name == "Stop" | project StopTime=timestamp, ActivityId) on ActivityId| project City, ActivityId, StartTime, StopTime, Duration = StopTime - StartTimelet Events = MyLogTable | where type=="Event" ;Events| where Name == "Start"| project Name, City, ActivityIdLeft = ActivityId, StartTime=timestamp| join (Events | where Name == "Stop" | project StopTime=timestamp, ActivityIdRight = ActivityId) on $left.ActivityIdLeft == $right.ActivityIdRight| project City, ActivityId, StartTime, StopTime, Duration = StopTime - StartTimeJoin flavors
The exact flavor of the join operator is specified with the kind keyword. The following flavors of the join operator are supported:
| Join kind/flavor | Description |
|---|---|
| innerunique (or empty as default) | Inner join with left side deduplication |
| inner | Standard inner join |
| leftouter | Left outer join |
| rightouter | Right outer join |
| fullouter | Full outer join |
| leftanti, anti, or leftantisemi | Left anti join |
| rightanti or rightantisemi | Right anti join |
| leftsemi | Left semi join |
| rightsemi | Right semi join |
Default join flavor
The default join flavor is an inner join with left side deduplication. Default join implementation is useful in typical log/trace analysis scenarios where you want to correlate two events, each matching some filtering criterion, under the same correlation ID. You want to get back all appearances of the phenomenon, and ignore multiple appearances of the contributing trace records.
X | join Y on Key X | join kind=innerunique Y on KeyThe following two sample tables are used to explain the operation of the join.
Table X
| Key | Value1 |
|---|---|
| a | 1 |
| b | 2 |
| b | 3 |
| c | 4 |
Table Y
| Key | Value2 |
|---|---|
| b | 10 |
| c | 20 |
| c | 30 |
| d | 40 |
The default join does an inner join after deduplicating the left side on the join key (deduplication keeps the first record).
Given this statement: X | join Y on Key
the effective left side of the join, table X after deduplication, would be:
| Key | Value1 |
|---|---|
| a | 1 |
| b | 2 |
| c | 4 |
and the result of the join would be:
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join Y on KeyOutput
| Key | Value1 | Key1 | Value2 |
|---|---|---|---|
| b | 2 | b | 10 |
| c | 4 | c | 20 |
| c | 4 | c | 30 |
Note
The keys 'a' and 'd' don't appear in the output, since there were no matching keys on both left and right sides.
Inner-join flavor
The inner-join function is like the standard inner-join from the SQL world. An output record is produced whenever a record on the left side has the same join key as the record on the right side.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=inner Y on KeyOutput
| Key | Value1 | Key1 | Value2 |
|---|---|---|---|
| b | 3 | b | 10 |
| b | 2 | b | 10 |
| c | 4 | c | 20 |
| c | 4 | c | 30 |
Note
- (b,10) from the right side, was joined twice: with both (b,2) and (b,3) on the left.
- (c,4) on the left side, was joined twice: with both (c,20) and (c,30) on the right.
Innerunique-join flavor
Use innerunique-join flavor to deduplicate keys from the left side. The result will be a row in the output from every combination of deduplicated left keys and right keys.
Note
innerunique flavor may yield two possible outputs and both are correct.In the first output, the join operator randomly selected the first key that appears in t1, with the value "val1.1" and matched it with t2 keys.In the second output, the join operator randomly selected the second key that appears in t1, with the value "val1.2" and matched it with t2 keys.
let t1 = datatable(key:long, value:string) [1, "val1.1", 1, "val1.2" ];let t2 = datatable(key:long, value:string) [ 1, "val1.3",1, "val1.4" ];t1| join kind = innerunique t2on keyOutput
| key | value | key1 | value1 |
|---|---|---|---|
| 1 | val1.1 | 1 | val1.3 |
| 1 | val1.1 | 1 | val1.4 |
let t1 = datatable(key:long, value:string) [1, "val1.1", 1, "val1.2" ];let t2 = datatable(key:long, value:string) [ 1, "val1.3", 1, "val1.4" ];t1| join kind = innerunique t2on keyOutput
| key | value | key1 | value1 |
|---|---|---|---|
| 1 | val1.2 | 1 | val1.3 |
| 1 | val1.2 | 1 | val1.4 |
Kusto is optimized to push filters that come after the
join, towards the appropriate join side, left or right, when possible.Sometimes, the flavor used is innerunique and the filter is propagated to the left side of the join. The flavor will be automatically propagated and the keys that apply to that filter will always appear in the output.
Use the example above and add a filter
where value == "val1.2". It will always give the second result and will never give the first result for the datasets:
let t1 = datatable(key:long, value:string) [1, "val1.1", 1, "val1.2" ];let t2 = datatable(key:long, value:string) [ 1, "val1.3", 1, "val1.4" ];t1| join kind = innerunique t2on key| where value == "val1.2"Output
| key | value | key1 | value1 |
|---|---|---|---|
| 1 | val1.2 | 1 | val1.3 |
| 1 | val1.2 | 1 | val1.4 |
Left outer-join flavor
The result of a left outer-join for tables X and Y always contains all records of the left table (X), even if the join condition doesn't find any matching record in the right table (Y).
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=leftouter Y on KeyOutput
| Key | Value1 | Key1 | Value2 |
|---|---|---|---|
| a | 1 | ||
| b | 2 | b | 10 |
| b | 3 | b | 10 |
| c | 4 | c | 20 |
| c | 4 | c | 30 |
Right outer-join flavor
The right outer-join flavor resembles the left outer-join, but the treatment of the tables is reversed.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=rightouter Y on KeyOutput
| Key | Value1 | Key1 | Value2 |
|---|---|---|---|
| b | 2 | b | 10 |
| b | 3 | b | 10 |
| c | 4 | c | 20 |
| c | 4 | c | 30 |
| d | 40 |
Full outer-join flavor
A full outer-join combines the effect of applying both left and right outer-joins. Whenever records in the joined tables don't match, the result set will have null values for every column of the table that lacks a matching row. For those records that do match, a single row will be produced in the result set, containing fields populated from both tables.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=fullouter Y on KeyOutput
| Key | Value1 | Key1 | Value2 |
|---|---|---|---|
| a | 1 | ||
| b | 2 | b | 10 |
| b | 3 | b | 10 |
| c | 4 | c | 20 |
| c | 4 | c | 30 |
| d | 40 |
Left anti-join flavor
Left anti-join returns all records from the left side that don't match any record from the right side.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=leftanti Y on KeyOutput
| Key | Value1 |
|---|---|
| a | 1 |
Note
Anti-join models the "NOT IN" query.
Right anti-join flavor
Right anti-join returns all records from the right side that don't match any record from the left side.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=rightanti Y on KeyOutput
| Key | Value2 |
|---|---|
| d | 40 |
Note
Anti-join models the "NOT IN" query.
Left semi-join flavor
Left semi-join returns all records from the left side that match a record from the right side. Only columns from the left side are returned.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=leftsemi Y on KeyOutput
| Key | Value1 |
|---|---|
| b | 2 |
| b | 3 |
| c | 4 |
Right semi-join flavor
Right semi-join returns all records from the right side that match a record from the left side. Only columns from the right side are returned.
let X = datatable(Key:string, Value1:long)[ 'a',1, 'b',2, 'b',3, 'c',4];let Y = datatable(Key:string, Value2:long)[ 'b',10, 'c',20, 'c',30, 'd',40];X | join kind=rightsemi Y on KeyOutput
| Key | Value2 |
|---|---|
| b | 10 |
| c | 20 |
| c | 30 |
Cross-join
Kusto doesn't natively provide a cross-join flavor. You can't mark the operator with the kind=cross.To simulate, use a dummy key.
X | extend dummy=1 | join kind=inner (Y | extend dummy=1) on dummy
Join hints
The join operator supports a number of hints that control the way a query runs.These hints don't change the semantic of join, but may affect its performance.
Join hints are explained in the following articles:
hint.shufflekey=<key>andhint.strategy=shuffle- shuffle queryhint.strategy=broadcast- broadcast joinhint.remote=<strategy>- cross-cluster join
FAQs
What are the different types of join? ›
- INNER JOIN.
- LEFT JOIN.
- RIGHT JOIN.
- FULL JOIN.
The Command instructs Azure Data Explorer to export the results of a given query into a blob storage, in a compressed format.
Which join flavor contains a row in the output for every combination of matching rows from left and right? ›Innerunique-join flavor
The result will be a row in the output from every combination of deduplicated left keys and right keys. innerunique flavor may yield two possible outputs and both are correct.
The UNION operator is used to combine the result-set of two or more SELECT statements.
How do I join two tables together? ›You can merge (combine) rows from one table into another simply by pasting the data in the first empty cells below the target table. The table will increase in size to include the new rows.
What is the most common join operation? ›The simplest and most common form of a join is the SQL inner join the default of the SQL join types used in most database management systems. It's the default SQL join you get when you use the join keyword by itself. The result of the SQL inner join includes rows from both the tables where the join conditions are met.
What are the join operations? ›JOIN Operation
Specifies a join between two tables with an explicit join clause, preserving unmatched rows from the first table. Specifies a join between two tables with an explicit join clause, preserving unmatched rows from the second table.
Four types of joins: left, right, inner, and outer.
How do I run a query in Azure Data Explorer? ›- In the Cluster connection pane, under the help cluster, select the Samples database.
- Copy and paste the following query into the query window. ...
- Copy and paste the following query into the query window, below the first query. ...
- Select the new query. ...
- Select Run or press Shift+Enter to run a query.
Azure Data Explorer is a fully-managed big data analytics cloud platform and data-exploration service, developed by Microsoft, that ingests structured, semi-structured (like JSON) and unstructured data (like free-text). The service then stores this data and answers analytic ad hoc queries on it with seconds of latency.
Can we join tables without primary key? ›
Yes, you can! The longer answer is yes, there are a few ways to combine two tables without a common column, including CROSS JOIN (Cartesian product) and UNION. The latter is technically not a join but can be handy for merging tables in SQL.
Which join gives all rows from both tables? ›A FULL JOIN or FULL OUTER JOIN is essentially a combination of LEFT JOIN and RIGHT JOIN . This type of join contains all of the rows from both of the tables.
Which join returns all records? ›The FULL OUTER JOIN keyword returns all records when there is a match in left (table1) or right (table2) table records.
How do you perform join operations on tables? ›(INNER) JOIN : Returns records that have matching values in both tables. LEFT (OUTER) JOIN : Returns all records from the left table, and the matched records from the right table. RIGHT (OUTER) JOIN : Returns all records from the right table, and the matched records from the left table.
What are the 5 different types of tables joins? ›We noted that Inner, Left, Right, and Full joins require mutual columns between tables while Cross join is to multiply to rows of the first table with the ones stored in the second table.
How to join two tables in SQL? ›The join is done by the JOIN operator. In the FROM clause, the name of the first table ( product ) is followed by a JOIN keyword then by the name of the second table ( category ). This is then followed by the keyword ON and by the condition for joining the rows from the different tables.
Can we join 2 tables without using join? ›You can replace the JOIN keyword with a comma in the FROM clause. What do you do next? There's no ON keyword for you to state the joining condition as there would be when using JOIN , e.g., on which two columns you want to join the tables. In this method, you simply use a WHERE clause to do so.
What is the most efficient way of joining 2 table in same database? ›Method 1: Relational Algebra
Relational algebra is the most common way of writing a query and also the most natural way to do so. The code is clean, easy to troubleshoot, and unsurprisingly, it is also the most efficient way to join two tables.
The most easiest and common way is to use join clause in the update statement and use multiple tables in the update statement. Here we can see that using join clause in update statement. We have merged two tables by the use of join clause.
What are the three types of join? ›- Cross join. A cross join returns all possible combinations of rows of two tables (also called a Cartesian product).
- Join/inner join. An inner join, also known as a simple join, returns rows from joined tables that have matching rows. ...
- Left outer join/left join.
- Right outer join/right join.
- Full outer join.
Which type of join is fastest? ›
In case there are a large number of rows in the tables and there is an index to use, INNER JOIN is generally faster than OUTER JOIN.
Which join is the best join? ›- Inner joins output the matching rows from the join condition in both of the tables.
- Cross join returns the Cartesian product of both tables.
- Outer join returns the matched and unmatched rows depending upon the left, right and full keywords.
- SQL self-join joins a table to itself.
In DBMS, a join statement is mainly used to combine two tables based on a specified common field between them. If we talk in terms of Relational algebra, it is the cartesian product of two tables followed by the selection operation.
Why We Use join operation? ›A join is an SQL operation performed to establish a connection between two or more database tables based on matching columns, thereby creating a relationship between the tables. Most complex queries in an SQL database management system involve join commands.
Why do we need join () method? ›Join method in Java allows one thread to wait until another thread completes its execution. In simpler words, it means it waits for the other thread to die. It has a void type and throws InterruptedException.
How many types of join operation are there? ›There are mainly two types of joins in DBMS 1) Inner Join 2) Outer Join. An inner join is the widely used join operation and can be considered as a default join-type.
How many rows does join return? ›A join is an operation that combines two rows together into one row.
What does (+) mean in SQL join? ›The plus sign is Oracle syntax for an outer join. There isn't a minus operator for joins. An outer join means return all rows from one table. Also return the rows from the outer joined where there's a match on the join key. If there's no matching row, return null.
What are the two ways you can execute a query in Azure? ›To run any query, expand a folder and choose the title of the query. The view opens to display the query Results. You can also run a query by using the Azure DevOps command line interface.
How does @query work? ›Queries help you find and work with your data
A query can either be a request for data results from your database or for action on the data, or for both. A query can give you an answer to a simple question, perform calculations, combine data from different tables, add, change, or delete data from a database.
How do I run an SQL query in Azure? ›
- On your SQL database Overview page in the Azure portal, select Query editor (preview) from the left menu.
- On the sign-in screen, provide credentials to connect to the database. You can connect using SQL authentication or Azure AD.
Azure Data Lake Storage is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you reduce your time to insight.
Where is data stored in Azure Data Explorer? ›Azure Data Explorer strictly adheres to this principle – all the persistent data is kept in Azure Blob Storage, and the data kept in Compute can be thought of as “merely” a cache of the data in Azure Blob.
Is Azure Data Explorer a time series database? ›ADX contains native support for creation, manipulation, and analysis of multiple time series. In this topic, learn how Azure Data Explorer is used to create and analyze thousands of time series in seconds, enabling near real-time monitoring solutions and workflows.
What is Azure Data Explorer in ADF? ›Azure Data Explorer now offers the Azure Data Factory (ADF), a fully-managed data integration service for analytic workloads in Azure, that empowers you to copy data from more than 80 data sources with a simple drag-and-drop experience.
Is Azure Data Explorer free? ›Free cluster allows anyone with a Microsoft account or an Azure Active Directory user identity to create a free Azure Data Explorer cluster without needing an Azure subscription or a credit card.
How do I visualize data in Azure? ›...
In the Query pane,
- Select the data source from the drop-down menu.
- Type the query, and the select Run. ...
- Select + Add visual.
Some common synonyms of join are associate, combine, connect, link, relate, and unite.
Can we join 2 tables without foreign key? ›Yes, you can join them using CROSS join which returns the cartesian product of tables in the query, so if you have 10 rows in each table then the query will return 100 rows.
What is difference between join and foreign key? ›A FOREIGN KEY enforces data integrity, making sure the data conforms to some rules when it is added to the DB. A JOIN is used when you extract/query data from the DB by giving rules how to select the data.
What is the difference between self join and cross join? ›
Inner join or Left join is used for self join to avoid errors. 2. Cross Join : Cross join allows us to join each and every row of both the tables.
What is the difference between a join and outer join operation? ›What is the difference between a join and an outer join operation? Explanation: The outer join operation preserves a few tuples that are otherwise lost in the join operation. The outer join operation preserves the tuples to the right of the operation.
What is difference between inner join and outer join? ›The biggest difference between an INNER JOIN and an OUTER JOIN is that the inner join will keep only the information from both tables that's related to each other (in the resulting table). An Outer Join, on the other hand, will also keep information that is not related to the other table in the resulting table.
Does full join return duplicates? ›Inner join will give you the records that have the same values in the joined columns between the 2 tables. From what you are saying, the 2 tables you are comparing are more or less the same, and full outer join giving you records from both tables, chances are you are going to get a lot of duplicates.
What is difference between join and inner join? ›Difference between JOIN and INNER JOIN
JOIN returns all rows from tables where the key record of one table is equal to the key records of another table. The INNER JOIN selects all rows from both participating tables as long as there is a match between the columns.
FULL JOIN: An Introduction
Unlike INNER JOIN , a FULL JOIN returns all the rows from both joined tables, whether they have a matching row or not. Hence, a FULL JOIN is also referred to as a FULL OUTER JOIN . A FULL JOIN returns unmatched rows from both tables as well as the overlap between them.
- Add a connection. You can do this in two different ways: Select the Connections tab, then select Add connection. Right-click on the Connections folder in the left navigation panel, then select Add connection.
- Select OK, and you should now be able to visualize the results of the query.
To get Superset to discover your new columns, all you have to do is to go to Data -> Datasets, click the edit icon next to the dataset whose schema has changed, and hit Sync columns from source from the Columns tab. Behind the scene, the new columns will get merged it.
What are connectors in Azure? ›When you build workflows using Azure Logic Apps, you can use connectors to help you quickly and easily access data, events, and resources in other apps, services, systems, protocols, and platforms - often without writing any code. A connector provides prebuilt operations that you can use as steps in your workflows.
How do you add a connection to a database? ›- Click the Connections tab .
- Click New connection and choose Database from the menu. The New connection window appears.
- Choose the database type you want to connect to. ...
- Provide the connection properties for your database. ...
- Click Add.
How do I use Kusto Explorer? ›
...
Share queries and results by email
- Run your query in Kusto. ...
- In the Home tab, in the Share section, select Export to Clipboard (or press Ctrl+Shift+C).
Method 1: Relational Algebra
Relational algebra is the most common way of writing a query and also the most natural way to do so. The code is clean, easy to troubleshoot, and unsurprisingly, it is also the most efficient way to join two tables.
Yes, you can! The longer answer is yes, there are a few ways to combine two tables without a common column, including CROSS JOIN (Cartesian product) and UNION. The latter is technically not a join but can be handy for merging tables in SQL.
How do you link two sets of data? ›In the Datasets panel, right-click the attribute you want to link and choose Link To Other Dataset. The Link Attributes Dialog opens. Linked attributes appear with a Link icon in the Datasets panel.