LoadFromGcs
Load data from GCS (Google Cloud Storage) to BigQuery
type: "io.kestra.plugin.gcp.bigquery.LoadFromGcs"Load an avro file from a gcs bucket
id: gcp_bq_load_from_gcs
namespace: company.team
tasks:
- id: http_download
type: io.kestra.plugin.core.http.Download
uri: https://huggingface.co/datasets/kestra/datasets/raw/main/csv/orders.csv
- id: csv_to_ion
type: io.kestra.plugin.serdes.csv.CsvToIon
from: "{{ outputs.http_download.uri }}"
header: true
- id: ion_to_avro
type: io.kestra.plugin.serdes.avro.IonToAvro
from: "{{ outputs.csv_to_ion.uri }}"
schema: |
{
"type": "record",
"name": "Order",
"namespace": "com.example.order",
"fields": [
{"name": "order_id", "type": "int"},
{"name": "customer_name", "type": "string"},
{"name": "customer_email", "type": "string"},
{"name": "product_id", "type": "int"},
{"name": "price", "type": "double"},
{"name": "quantity", "type": "int"},
{"name": "total", "type": "double"}
]
}
- id: load_from_gcs
type: io.kestra.plugin.gcp.bigquery.LoadFromGcs
from:
- "{{ outputs.ion_to_avro.uri }}"
destinationTable: "my_project.my_dataset.my_table"
format: AVRO
avroOptions:
useAvroLogicalTypes: true
Load a csv file with a defined schema
id: gcp_bq_load_files_test
namespace: company.team
tasks:
- id: load_files_test
type: io.kestra.plugin.gcp.bigquery.LoadFromGcs
destinationTable: "myDataset.myTable"
ignoreUnknownValues: true
schema:
fields:
- name: colA
type: STRING
- name: colB
type: NUMERIC
- name: colC
type: STRING
format: CSV
csvOptions:
allowJaggedRows: true
encoding: UTF-8
fieldDelimiter: ","
from:
- gs://myBucket/myFile.csv
Avro parsing options.
The clustering specification for the destination table.
Whether the job is allowed to create tables.
Csv parsing options.
The table where to put query results.
If not provided, a new table is created.
The source format, and possibly some parsing options, of the external data.
Google Cloud Storage source data
The fully-qualified URIs that point to source data in Google Cloud Storage (e.g. gs://bucket/path). Each URI can contain one '*' wildcard character and it must come after the 'bucket' name.
The GCP service account to impersonate.
The geographic location where the dataset should reside.
This property is experimental and might be subject to change or removed.
See Dataset Location
The GCP project ID.
The messages which would trigger an automatic retry.
Message is tested as a substring of the full message, and is case insensitive.
The reasons which would trigger an automatic retry.
The schema for the destination table.
The schema can be omitted if the destination table already exists, or if you're loading data from a Google Cloud Datastore backup (i.e. DATASTORE_BACKUP format option).
schema:
fields:
- name: colA
type: STRING
- name: colB
type: NUMERIC
See type from StandardSQLTypeName
Experimental Options allowing the schema of the destination table to be updated as a side effect of the query job.
Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema.
The GCP scopes to be used.
The GCP service account.
The time partitioning field for the destination table.
The time partitioning type specification for the destination table.
The action that should occur if the destination table already exists.
Destination table
The job id
Output rows count
The character encoding of the data.
The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values set in {@link #setQuote(String)} and {@link #setFieldDelimiter(String)}.
The separator for fields in a CSV file.
BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
The value that is used to quote data sections in a CSV file.
BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set {@link #setAllowQuotedNewLines(boolean)} property to {@code true}.