BigQuery - remove unused column from schema
I accidentally added a wrong column to my BigQuery table schema.
Instead of reloading the complete table (million of rows), I would like to know if the following is possible:
- remove bad rows (rows with values contains the wrong column) by running a "select *" query on the table with some kind of filter, and saving result to same table.
- removing the (now) unused column.
Is this functionality (or similar) supported? Possibly the "save result to table" functionality can have a "compact schema" option.
If your table does not consist of record/repeated type fields - your simple option is:
Select valid columns while filtering out bad records into new temp table
SELECT < list of original columns > FROM YourTable WHERE < filter to remove bad entries here >
Write above to temp table -
Make a backup copy of "broken" table -
- Check if all looks as expected and if so - get rid of temp and backup tables
Please note: the cost of above #1 is exactly the same as action in first bullet in your question. The rest of actions (copy) are free
In case if you have repeated/record fields - you still can execute above plan, but in #1 you will need to use some BigQuery User-Defined Functions to have proper schema in output You can see below for examples - of course this will require some extra dev - but if you are in critical situation - this should work for you
Create a table with Record type column create a table with a column type RECORD
I hope, at some point Google BigQuery Team will add better support for cases like yours when you need to manipulate and output repeated/record data, but for now this is a best workaround I found - at least for myself
Modifying table schemas | BigQuery, I accidentally added a wrong column to my BigQuery table schema. Instead of reloading the complete table (million of rows), I would like to know if the following � You can also remove a column by exporting your table data to Cloud Storage, deleting the data corresponding to the column (or columns) you want to remove, and then loading the data into a new table
Save results to table is your way to go. Try on the big table with the selected columns you are interested, and you can apply a limit to make it small.
BigQuery - remove unused column from schema, As of writing this will remove any table history so be very careful of what you are doing. Please be sure that you backup your critical data and test� If the data you're appending is in CSV or newline-delimited JSON format, specify the relaxed columns in a local JSON schema file or use the --autodetect flag to use schema detection to discover relaxed columns in the source data. For information on relaxing column modes using a JSON schema file, see Manually changing REQUIRED columns to NULLABLE.
Below is the code to do it. Lets say c is the column that you wants to delete.
CREATE OR REPLACE TABLE transactions.test_table AS SELECT * EXCEPT (c) FROM transactions.test_table;
Or second method and my favorite is by following below steps.
- Write Select query with the columns you want to exclude.
- Go to Query Settings Query Settings
- In Destination setting Set destination table for query results, enter project name, Dataset name and table name exactly same as you entered in Step 1.
- In Destination table write preference select Overwrite table. Destination table settings
- Save the Query Setting and run the query.
BigQuery Drop or Change Column. BigQuery DDL doesn't support , Another fix could be to specify explicitly the schema for each column and change section, we learn that we need a reusable function to clean up numeric data: BigQuery DDL doesn’t support altering tables, but it does support re-writing tables. You can use this to achieve the same effect. As of writing this will remove any table history so be very
4. Loading Data into BigQuery, Args: projectId: string, Project ID of the table to delete (required) datasetId: string If you leave this list empty, all column families are present in the table schema� The second option is to export the data to Cloud Storage and from there return it to BigQuery with the correct mode for all columns. How to remove a column from the data schema. Use the SELECT * EXCEPT query to exclude a column (or columns), then write the query results to the old table or create a new one. Request example:
BigQuery API . tables, schema (Optional[Sequence[Union[ \ :class:`~google.cloud.bigquery.schema. SchemaField` To delete a label, set its value to :data:`None` before updating. Raises: according to the schema. Raises: ValueError: If schema is empty. Table` populated with row data and column headers from the query results. The column� google-bigquery - delete - bigquery rename column Bigquery add columns to table schema (2) I was stuck trying to add columns to an existing table in BigQuery using the Python client and found this post several times.
Source code for google.cloud.bigquery.table, When you create an empty table in BigQuery, you need to set the schema manually. This can be done How to remove a column from the data schema. Use the� BigQuery INFORMATION_SCHEMA is subject to the following limitations: BigQuery INFORMATION_SCHEMA queries must be in standard SQL syntax. INFORMATION_SCHEMA does not support legacy SQL. INFORMATION_SCHEMA query results are not cached. Currently, INFORMATION_SCHEMA cannot be used to retrieve metadata on partitions in partitioned tables.