![]() To get details about specific tables in the dataset, pull the table name and include in the following query like this example using the posts_questions table from the stackoverflow dataset. When merging, I can leave off project_id and table_catalog since they are redundant. ![]() I also changed table_id to table_name to make it easier to merge with the first query in this post. SELECT project_id, dataset_id, table_id as table_name, CAST(TIMESTAMP_MILLIS(creation_time) AS DATETIME) as creation_time, CAST(TIMESTAMP_MILLIS(last_modified_time) AS DATETIME) as last_modified_time, row_count, size_bytes / POW(10,9) as GB, type FROM bigquery-public-data.stackoverflow._TABLES_ In the above query, I modified the query as follows to make changes so timestamp was in datetime format and and size_bytes were GB. table_id (same as table_name in schema).dataset_id (same as table_schema in schema).project_id (same as table_catalog in schema).Query processed 0B when run and column results include: Note, its two underscores on both sides of the TABLES above. SELECT * FROM bigquery-public-data.stackoverflow._TABLES_ Query processed 10MB when run and column results include:Īdditional table details including number of rows and table data size. Get a list of all tables in the dataset and the corresponding information. Change out the names as needed for the dataset and tables you are working with. In the following examples, I’m using the BigQuery public Stack Overflow database to demonstrate these commands. This is a quick bit to share queries you can use to pull metadata on your datasets and tables. crt file.When working with tables in BigQuery, you need an understanding of a dataset structure whether it is public or you set it up and you want to review. Use the available DER link to download the certificate as a. The following example assumes that you have OpenSSL installed. To do the conversion you will need to have an SSL software installed such as OpenSSL. If you do not have an appropriate storage certificate to use with the connector in your Windows environment, you will need to download one and convert it into a. If a string is longer than the set value, it will be truncated, and the exceeding characters will not be loaded. Setting this value close to the maximum length may improve load times, as it limits the need to allocate unnecessary resources. This can be set from 256 to 16384 characters. If not selected, data will be loaded row by row. This may result in faster load times for larger datasets. Select this to include larger portions of data in the iterations within a load. Load properties that can be configured Property If you are connecting through a proxy server you must provide authentication information for the proxy server. For example, if TLS 1.1 is specified, TLS 1.0 cannot be used. The minimum version of TLS allowed for encrypting connections. The Google BigQuery Connector supports multiple catalogs, the equivalent of Google BigQuery projects. ![]() ![]() This project is the default project the Google BigQuery Connector queries against. The specified value is the password your key file is encrypted with. This option allows you to use a P12 private key file with a non-standard password. Validates the confirmation code or the key. Yes, when Service Authentication is selected. The code obtained from the Google sign-in page. Yes, when User Authentication is selected. Redirects to a Google sign-in page where you can obtain a confirmation code. Read more about how to configure permissions for the Google service account in the Google documentation. Select User Authentication or Service Authentication mechanisms.įor Service Authentication, the Google service account must be BigQuery Job User for connections to multiple catalogs, or BigQuery Data Viewer for connections to a single catalog. Account properties that can be configured Account property ![]()
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