This component integrates with the 'YouTube Data API' (https://developers.google.com/youtube/v3/docs/) to retrieve data from YouTube and load it into a table.
Warning: This component is destructive as it truncates or recreates its target table on each run. Do not modify the target table structure manually.
|Name||Text||The descriptive name for the component.|
|Basic/Advanced Mode||Choice||Basic: This mode will build a 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 to call data from YouTube.
|Authentication||Choice||Select an authentication method, which must be setup in advance.
Snowflakeuses 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 from the server. (Property only available in Basic Mode)|
|Data Selection||Choice||Select one or more columns to return from the query. (Property only available in Basic Mode)|
|Data Source Filter||Input Column||The available input columns vary depending upon the Data Source. (Property only available in Basic Mode)|
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||Text||Custom SQL-like query. (Property only available during 'Advanced' mode)|
|Combine Filters||Text||Use the defined filters in combination with one another according to either "and" or "or".|
|Limit||Number||Limits the number of rows that are loaded from file.|
|Connection Options||Parameter||A JDBC parameter supported by the Database Driver. The available parameters are explained in the Data Model.
These are usually not required as sensible defaults are assumed.
|Value||A value for the given Parameter.|
|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.
|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.
|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.|
|Distribution Style||Select||Auto: (Default) Allow Redshift to manage your distribution style.
Even: Distributes 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.
|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.
|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:
|Component||Name of the component.|
|Status||Successful or Unsuccessful.|
|Started At||Time Component began.|
|Completed At||Time Component finished.|
|Duration||Duration of Component's run.|
|Row Count||Number of Rows queried by the component.|
|Message||Any messages yielded by the component (usually empty).|
Connect to the target database and issue the query. Stream the results into objects on a storage bucket. Then create or truncate the target table and issue a COPY command to load the bucket objects into the table. Finally, clean up the temporary objects left in the storage bucket
In this example, the YouTube Query Component is used to source data on YouTube video statistics. The following job is used to create a table named 'yt_stats' and load it with data.
A 'Create/Replace Table' Component is used to create the 'yt_stats' table, immediately followed by the YouTube Query Component. The properties for the YouTube Query Component can be seen below.
The YouTube Query Component is set to 'Advanced' Mode, allowing a custom SQL query that takes a selection from 'videos' - a view in the CDATA YouTube Data Model that defaults to giving 200 (randomly selected) currently-trending videos from YouTube.
The job is completed with a Run Transformation Component that links to a Transformation job named 'YouTube. This Transformation job will take video data we have loaded and filter it such that only music videos remain. The Transformation job layout is given below.
A Table Input component is used to load the 'yt_stats' table and allows us to inspect a sample through the 'Sample' tab.
A Filter Component is then used to take only rows where the categoryid is equal to '10' (10 being an ID for the music video category).
When our jobs are run, the Filter Component's Sample tab now shows our finished data, giving us the latest trending music videos on YouTube.