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LoadJobConfiguration; import com. Schema; import com. Before trying this sample, follow the Node. For more information, see the BigQuery Node.

Before trying this sample, follow the PHP setup instructions in the BigQuery quickstart using client libraries. Before trying this sample, follow the Python setup instructions in the BigQuery quickstart using client libraries. Before trying this sample, follow the Ruby setup instructions in the BigQuery quickstart using client libraries.

Waits for table load to complete. This table contains information about people. It consists of the following fields:. The JSON data file would look like the following. Notice that the address field contains an array of values indicated by [ ]. For information on specifying a nested and repeated schema, see Specifying nested and repeated fields. You can load additional data into a table either from source files or by appending query results. In the Cloud Console, use the Write preference option to specify what action to take when you load data from a source file or from a query result.

If you load data into an existing table, the load job can append the data or overwrite the table. The Cloud Storage bucket must be in the same location as the dataset that contains the table you're appending or overwriting. In the Table name field, enter the name of the table you're appending or overwriting in BigQuery. For Partition and cluster settings , leave the default values. You cannot convert a table to a partitioned or clustered table by appending or overwriting it, and the Cloud Console does not support appending to or overwriting partitioned or clustered tables in a load job.

If you leave the Google-managed key setting, BigQuery encrypts the data at rest. Specify the --replace flag to overwrite the table. Use the --noreplace flag to append data to the table. If no flag is specified, the default is to append data. It is possible to modify the table's schema when you append or overwrite it.

For more information on supported schema changes during a load operation, see Modifying table schemas. The schema is defined using schema auto-detection. The schema is defined using a JSON schema file — myschema. You can include multiple URIs as a comma-separated list. Note that wildcards are also supported.

Specify the data format by setting the configuration. Specify the write preference by setting the configuration. To replace the rows in an existing table, set the LoadJobConfig. To replace the rows in an existing table, set the write parameter of Table.

BigQuery supports loading hive partitioned JSON data stored on Cloud Storage and populates the hive partitioning columns as columns in the destination BigQuery managed table. For more information, see Loading externally partitioned data. BigQuery can parse any of the following pairs for Boolean data: 1 or 0, true or false, t or f, yes or no, or y or n all case insensitive.

Schema autodetection will automatically detect any of these except 0 and 1. BigQuery accepts a variety of timestamp formats. The timestamp must include a date portion and a time portion. For more information, see Time zones. If you provide a schema, BigQuery also accepts Unix Epoch time for timestamp values. However, schema autodetection will not detect this case, and will treat the value as a numeric or string type instead.

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