QlikView Join Functions

Using join functions in QlikView, data from two or more tables can be combined based on shared field values. QlikView has inner joins, outer joins, and cross joins, among other sorts of join methods.

Rows from two tables that have matching values in a common field are combined by an inner join. Only rows with matches in both tables will be included in the resulting table.

Outer join: An outer join merges all rows from two tables, even those whose common field values are not identical. There are three different kinds of outer joins: full, right, and left outer joins.

A left outer join combines every row from the left table with any matching rows from the right table. 

A right outer join includes every row from the right table as well as any matching rows from the left table. The left table’s columns in the final table will have NULL values if there are no matching rows in the left table.

Full outer join: A full outer join includes all rows from both tables, regardless of whether there are matching values in the common field. If there are no matching rows in either table, the resulting table will include NULL values in the corresponding columns.

Every row from one table is combined with every row from another table in a cross-join. All conceivable combinations of rows from both tables will be included in the final table.

To use join functions in QlikView, you can use the JOIN statement in the Data Load Editor.

For example:

LOAD *
FROM Table1.qvd (qvd)
LEFT JOIN Table2.qvd (qvd)
ON Table1.Field1 = Table2.Field1;

This will create a left outer join between Table1 and Table2, using the common field Field1. The resulting table will include all rows from Table1, and any matching rows from Table2. If there are no matching rows in Table 2, the resulting table will include NULL values in Table 2’s columns.
QlikView has several join functions that can be used to combine data from multiple tables. The most commonly used join functions are:

1. “JOIN” – This function is used to join two or more tables based on a common field. The common field is known as the “join key”, and it must have the same name and data type in both tables. The “JOIN” function can be used with the “LOAD” statement to load data from multiple tables into a single table.

For example:

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LOAD *
FROM orders.csv (txt, utf8, embedded labels, a delimiter is ',')
JOIN
LOAD *
FROM customers.csv (txt, utf8, embedded labels, a delimiter is ',')
ON orders.customer_id = customers.customer_id;

2. “LEFT JOIN” – This function is used to join two or more tables based on a common field, but it also includes all rows from the left table, even if there is no match in the right table.

For example:

vbnetCopy code
LOAD *
FROM orders.csv (txt, utf8, embedded labels, delimiter is ',')
LEFT JOIN
LOAD *
FROM customers.csv (txt, utf8, embedded labels, delimiter is ',')
ON orders.customer_id = customers.customer_id;

3. “RIGHT JOIN” – This function is used to join two or more tables based on a common field, but it also includes all rows from the right table, even if there is no match in the left table.

For example:

vbnetCopy code
LOAD *
FROM orders.csv (txt, utf8, embedded labels, delimiter is ',')
RIGHT JOIN
LOAD *
FROM customers.csv (txt, utf8, embedded labels, delimiter is ',')
ON orders.customer_id = customers.customer_id;

4. “FULL OUTER JOIN” – This function is used to join two or more tables based on a common field, and it includes all rows from both tables, even if there is no match in the other table.

For example:

vbnetCopy code
LOAD *
FROM orders.csv (txt, utf8, embedded labels, delimiter is ',')
FULL OUTER JOIN
LOAD *
FROM customers.csv (txt, utf8, embedded labels, delimiter is ',')
ON orders.customer_id = customers.customer_id;

5. “MAP JOIN” – This function is used to join two or more tables based on a common field and it can be used to join large data sets efficiently

For example:

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MAP JOIN(tablename1, tablename2, join_field1, join_field2);

These join functions can be used to combine data from multiple tables and create a single table that contains all of the data. The join function you choose will depend on the specific requirements of your data and the type of join that best suits your needs.