Square Query Component
This component uses the Square API to retrieve data and load it into a table. This stages the data, so the table is reloaded each time. You may then use transformations to enrich and manage the data in permanent tables.
The component offers both a Basic and Advanced mode (see below) for generating the Square API query. Note however that although this is exposed in an SQL-like language, the exact semantics can be surprising - for example filtering on a column can return more data than not filtering on it, an impossible scenario with regular SQL.
There are some special pseudo columns which can be part of a query filter, but are not returned as data. This is fully described in the data model.
Warning: This component is destructive as it truncates or recreates its target table on each run. Do not modify the target table structure manually.
It is vital that the Square Query component is configured such that a default LocationId is defined. This can be done either through SQL, Data Source Filter or through the Connection Options property.
- SQL: In 'Advanced' mode, custom SQL Queries can be written and may include a clause such as 'where locationid = 'D84SJKFUI39E' where the LocationId is defined.
- Data Source Filter:If the LocationId column is pulled in using the Data Source property, it can be defined through a filter such as 'LocationId, Is, Equal To, D84SJKFUI39E'
- Connection Options:A connection string 'LocationId' also exists that allows the default LocationId to be set through the Connection Options Property.
The 'locations' table can be queried to find valid values of LocationId for the above purposes. Such queries can be done through the 'Basic' component setup by selecting the 'Locations' Data Source. Failure to provide a default LocationId for the component will result in the error 'Provide a LocationId in the query or connection string' when the component is run.
|Name||Text||The descriptive name for the component.|
Basic - This mode will build a Square Query for you using settings from Data Source, Data Selection
and Data Source Filter parameters. In most cases, this will be sufficient.
Advanced - This mode will require you to write an SQL-like query which is translated into one or more Square queries.
|Authentication||Choice||Select an authentication method, which must be setup in advance. Square uses the OAuth standard for authenticating 3rd party applications. More help is provided in the setup screens for OAuth authentication.|
|Data Source||Choice||Select a data source.|
|Data Selection||Choice||Select one or more columns to return from the query.|
|Data Source Filter||Input Column||The available input columns vary depending upon the Data Source.|
Is - Compares the column to the value using the comparator.
Not - Reverses the effect of the comparison, so "equals" becomes "not equals", "less than" becomes "greater than or equal to", etc.
|Comparator||Choose a method of comparing the column to the value. Possible comparators include: 'Equal To', 'Greater than', 'Less than', 'Greater than or equal to', 'Less than or equal to', 'Like', 'Null'.
'Equal To' can match exact strings and numeric values while other comparators such as 'Greater than' will work only with numerics. The 'Like' operator allows the wildcard character (%) to be used at the start and end of a string value to match a column. The Null operator matches only Null values, ignoring whatever the value is set to.
Not all data sources support all comparators, thus it is likely only a subset of the above comparators will be available to choose from.
|Value||The value to be compared.|
|SQL Query||Text||This is an SQL-like query, written according to the Square data model.|
|Combine Filters||Text||Use the defined filters in combination with one another according to either "and" or "or".|
|Limit||Number||Fetching a large number of results from Square will use multiple API calls. These calls are rate-limited by the provider, so fetching a very large number may result in errors.|
|Connection Options||Parameter||A JDBC parameter supported by the Database Driver. The available parameters are determined automatically from the driver, and may change from version to version. Parameters can be found in the data model, found here.
They are usually not required as sensible defaults are assumed.
|Value||A value for the given Parameter. The parameters and allowed values for the Square data model are Connection String Options as
|Warehouse||Select||Choose a Snowflake warehouse that will run the load.|
|Database||Select||Choose a database to create the new table in.|
|Type||Select||Choose between using a standard table or an external table.
Standard: The data will be staged on an S3 bucket before being loaded into a table.
External: The data will be put into an S3 Bucket and referenced by an external table.
|Schema||Select||Select the table schema. The special value, [Environment Default] will use the schema defined in the environment. For more information on using multiple schemas, see this article.
Note: An external schema is required if the 'Type' property is set to 'External'.
|Target Table||Text||Provide a new table name.
Warning: This table will be recreated and will drop any existing table of the same name.
|Storage Account||Select||(Azure Only) Select a Storage Account with your desired Blob Container to be used for staging the data.|
|Blob Container||Select||(Azure Only) Select a Blob Container to be used for staging the data.|
(AWS Only) Snowflake Managed: Allow Matillion ETL to create and use a temporary internal stage on Snowflake for staging the data. This stage, along with the staged data, will cease to exist after loading is complete.
Existing Amazon S3 Location: Selecting this will avail the user of properties to specify a custom staging area on S3.
|S3 Staging Area||Text||(AWS Only) The name of an S3 bucket for temporary storage. Ensure
your access credentials have S3 access and permission to write
to the bucket. See this document for
details on setting up access. The temporary objects created in this bucket will be removed again after the load completes, they are not kept.
This property is available when using an Existing Amazon S3 Location for Staging.
|Location||Text/Select||When using an 'External' type table, Provide an S3 Bucket path that will be used to store the data. Once on an S3 bucket, the data can be referenced by the external table.|
Even - the default option, distribute rows around the Redshift Cluster evenly.
All - copy rows to all nodes in the Redshift Cluster.
Key - distribute rows around the Redshift cluster according to the value of a key column.
Table-distribution is critical to good performance - see the Amazon Redshift documentation for more information.
|Table Distribution Key||Select||This is only displayed if the Table Distribution Style is set to Key. It is the column used to determine which cluster node the row is stored on.|
|Sort Key||Select||This is optional and specifies the columns from the input that should be set as the table's sort-key.
Sort-keys are critical to good performance - see the Amazon Redshift documentation for more information.
|Sort Key Options||Select||Decide whether the sort key is of a compound or interleaved variety - see the Amazon Redshift documentation for more information.|
|Project||Text||The target BigQuery project to load data into.|
|Dataset||Text||The target BigQuery dataset to load data into.|
|Cloud Storage Staging Area||Text||The URL and path of the target Google Storage bucket to be used for staging the queried data.|
|Encryption||Select||(AWS Only) Decide on how the files are encrypted inside the S3 Bucket.This property is available when using an Existing Amazon S3 Location for Staging.
None: No encryption.
SSE KMS: Encrypt the data according to a key stored on KMS.
SSE S3: Encrypt the data according to a key stored on an S3 bucket
|KMS Key ID||Select||(AWS Only) The ID of the KMS encryption key you have chosen to use in the 'Encryption' property.|
|Load Options||Multiple Selection||
Comp Update: Apply automatic compression to the target table (if ON). Default is ON.
Stat Update: Automatically update statistics when filling a table (if ON). Default is ON. In this case, it is updating the statistics of the target table.
Clean S3 Objects: Automatically remove UUID-based objects on the S3 Bucket (if ON). Default is ON. Effectively decides whether to keep the staged data in the S3 Bucket or not.
String Null is Null: Converts any strings equal to "null" into a null value. This is case sensitive and only works with entirely lower-case strings. Default is ON.
Recreate Target Table:Choose whether the component recreates its target table before the data load. If OFF, the existing table will be used. Default is ON.
|Load Options||Multiple Select||Clean Cloud Storage Files: (If On) Destroy staged files on Cloud Storage after loading data. Default is On.
Cloud Storage File Prefix: Give staged file names a prefix of your choice. Default is empty (no prefix).
|Auto Debug||Select||Choose whether to automatically log debug information about your load. These logs can be found in the Task History and should be included in support requests concerning the component. Turning this on will override any debugging Connection Options.|
|Debug Level||Select||The level of verbosity with which your debug information is logged. Levels above 1 can log huge amounts of data and result in slower execution.
1: Will log the query, the number of rows returned by it, the start of execution and the time taken, and any errors.
2: Will log everything included in Level 1, cache queries, and additional information about the request, if applicable.
3: Will additionally log the body of the request and the response.
4: Will additionally log transport-level communication with the data source. This includes SSL negotiation.
5: Will additionally log communication with the data source and additional details that may be helpful in troubleshooting problems. This includes interface commands.
This component makes the following values available to export into variables:
|Time Taken To Stage||The amount of time (in seconds) taken to fetch the data from the data source and upload it to storage.|
|Time Taken To Load||The amount of time (in seconds) taken to load the data into the target table from the staging area.|
Connect to the Square Server and issue the one or more queries. Stream the results into objects into a storage area, recreate or truncate the target table as necessary and then use a COPY command to load the stored objects into the table. Finally, clean up the temporary stored objects.
In this example, we use Matillion ETL to load customer data from Square. To do this, however, we must first retrieve the LocationID of the account we wish to pull data from. We can accomplish this by running the Square Query location in 'Basic' mode and choosing the 'Locations' data source. Alternatively, we can run the following query in 'Advanced' mode:
SELECT * FROM Locations
These are then stored in the table 'locations'. Right-clicking on the component and selecting 'Run Component' allows us to quickly run this query.
In this example, we have only a single location that we can easily retrieve by sampling the table in a Table Input component.
Using this LocationID, we can now load the location data using a job such as below.
The Square Query component in this job is set up as follows. Note that the LocationID is now set in the 'Connection Options' property.
Using a Table Input component inside a Transformation job allows us to sample the table and ensure the load has run correctly.