Left Join in Tableau Desktop |Tableau Community Forums
How to determine whether to join tables or use data blending. data type match, and it automatically creates a data relationship between them. Can i define a data relationship between two data sources as a there is a way to define a between join while defining the Data relationships. How to create one-to-many relationships in Tableau Desktop. When joining multiple large tables, the data duplication can slow performance.
Union data from within a connection To union data, you must use text tables or Excel tables from the same connection. That is, you cannot union tables from different databases. In Tableau Desktop, you can union tables across different Excel workbooks and files in different folders. For more information, see the Union tables using wildcard search Tableau Desktop.
If you need to union data from different databases, use Tableau Prep. Collation Collation refers to the rules of a database that determine how string values should be compared and sorted. In most cases, the collation is handled by the database.
Between join in Edit Data Relationships |Tableau Community Forums
However, when you work with cross-database joins, you might join columns that have different collations. For example, suppose your cross-database join used a join key comprised of a case-sensitive column from SQL Server and a case-insensitive column from Oracle. In cases like this, Tableau maps certain collations to others to minimize interpreting values incorrectly.
The following rules are used in cross-database joins: If all columns use collation standards of the ICU, Tableau uses the collation of the column of the left table.
If no columns use collation standards of the ICU, Tableau uses a binary collation. A binary collation means the locale of the database and data type of the columns determine how string values should be compared and sorted. Collation of Japanese characters, that is, Kana-sensitivity, depends on the database that you are connected to. Calculations and multi-connection data sources Only a subset of calculations can be used in a multi-connection data source.
You can use a specific calculation if it is both: Supported by all the connections in the multi-connection data source Supported by Tableau extracts. In web authoring Tableau Online and Tableau Server: You can use a specific calculation if it is supported by all the connections in the multi-connection data source.
Stored procedures Stored procedures are not available for multi-connection data sources. Pivot data from within a connection To pivot data, you must use text columns or Excel columns from the same connection. That is, you cannot include columns from different databases in a pivot. Make extract files the first connection Tableau Desktop only When connecting to extract files in a multi-connection data source, make sure that the connection to the extract. This preserves any customizations that might be a part of the extract, including changes to default properties, calculated fields, groups, aliases, etc.
If you need to connect to multiple extract files in your multi-connection data source, only the customizations in the extract in the first connection are preserved. Extracts of multi-connection data sources that contain connections to file-based data Tableau Desktop only If you're publishing an extract of a multi-connection data source that contains a connection to file-based data such as Excel, selecting the Include external files option puts a copy of the file-based data on the server as part of the data source.
- Join Your Data
In this case, a copy of your file-based data can be downloaded and its contents accessed by other users. If there is sensitive information in the file-based data that you have intentionally excluded from your extract, do not select Include external files when you publish the data source. For more information about publishing data sources, see Publish a Data Source.
About queries and cross-database joins For each connection, Tableau sends independent queries to the databases in the join. The results are stored in a temporary table, in the format of an extract file.
For example, suppose you create connections to two tables, dbo. Tableau queries the database in each connection independently. The database performs the query and applies customizations such as filters and calculations, and Tableau stores the results for each connection in a temporary table.
These temporary tables are necessary for Tableau to perform cross-database joins. After the tables have been joined, "topn" filter is applied to limit the number of values shown in the data grid to the first 1, rows.
Blend Your Data
This filter is applied to help maintain responsiveness of the data grid and the overall performance of the Data Source page.
Joined tables Review join results in the data grid After you have created a join on the canvas, review the data grid to make sure the join produces the results that you expect. If the data grid displays data that you don't expect, you might need to modify the join. Results in the data grid No data: If no data displays in the data grid, you might need to change the join type or a join field used in the join condition.
If you suspect a mismatch between fields in the join, use a calculation instead. For more information, see Use calculations to resolve mismatches between fields in a join. When you blend on a field with a high level of granularity, for example, date instead of year, queries can be slow. Prerequisites for data blending Your data must meet the following requirements in order for you to use data blending.
Primary and secondary data sources Data blending requires a primary data source and at least one secondary data source. When you designate a primary data source, it functions as the main table or main data source. Any subsequent data sources that you use on the sheet are treated as a secondary data source. Only columns from the secondary data source that have corresponding matches in the primary data source appear in the view.
Using the same example from above, you designate the transactional data as the primary data source and the quota data as the secondary data source. Cube multidimensional data sources must be used as the primary data source. Cube data sources cannot be used as a secondary data source. Defined relationship between the primary and secondary data sources After designating primary and secondary data sources, you must define the common dimension or dimensions between the two data sources.
This common dimension is called the linking field. Continuing the example from above, when you blend transactional and quota data, the date field might be the linking field between the primary and secondary data sources. If the date field in the primary and secondary data sources have the same name, Tableau creates the relationship between the two fields and shows a link icon next to the date field in the secondary data source when the field is in the view.
Differences between joins and data blending Data blending simulates a traditional left join. The main difference between the two is when the join is performed with respect to aggregation.
Left join When you use a left join to combine data, a query is sent to the database where the join is performed. Using a left join returns all rows from the left table and any rows from the right table that has a corresponding row match in the left table. The results of the join are then sent back to and aggregated by Tableau.
For example, suppose you have the following tables. Data blending When you use data blending to combine data, a query is sent to the database for each data source that is used on the sheet. The results of the queries, including the aggregated data, are sent back to and combined by Tableau.
The view uses all rows from the primary data source, the left table, and the aggregated rows from the secondary data source, the right table, based on the dimension of the linking fields. Dimension values are aggregated using the ATTR aggregate function, which means the aggregation returns a single value for all rows in the secondary data source.
Measure values are aggregated based on how the field is aggregated in the view. You can change the linking field or add more linking fields to include different or additional rows of data from the secondary data source in the blend, changing the aggregated values.
In this case, not all values can be a part of the resulting table because of the following: