Google BigQuery output plugin

• Plugin version: v4.6.0
• Released on: 2024-09-16
• Changelog

For other versions, see the Versioned plugin docs.

For plugins not bundled by default, it is easy to install by running bin/logstash-plugin install logstash-output-google_bigquery. See Working with plugins for more details.

For questions about the plugin, open a topic in the Discuss forums. For bugs or feature requests, open an issue in Github. For the list of Elastic supported plugins, please consult the Elastic Support Matrix.

This Logstash plugin uploads events to Google BigQuery using the streaming API so data can become available to query nearly immediately.

You can configure it to flush periodically, after N events or after a certain amount of data is ingested.

You must enable BigQuery on your Google Cloud account and create a dataset to hold the tables this plugin generates.

You must also grant the service account this plugin uses access to the dataset.

You can use Logstash conditionals and multiple configuration blocks to upload events with different structures.

This is an example of Logstash config:

output {
   google_bigquery {
     project_id => "folkloric-guru-278"                        (required)
     dataset => "logs"                                         (required)
     csv_schema => "path:STRING,status:INTEGER,score:FLOAT"    (required) 1
     json_key_file => "/path/to/key.json"                      (optional) 2
     error_directory => "/tmp/bigquery-errors"                 (required)
     date_pattern => "%Y-%m-%dT%H:00"                          (optional)
     flush_interval_secs => 30                                 (optional)
   }
}

1. Specify either a csv_schema or a json_schema.
2. If the key is not used, then the plugin tries to find Application Default Credentials

• There is a small fee to insert data into BigQuery using the streaming API.
• This plugin buffers events in-memory, so make sure the flush configurations are appropriate for your use-case and consider using Logstash Persistent Queues.
• Events will be flushed when batch_size, batch_size_bytes, or flush_interval_secs is met, whatever comes first. If you notice a delay in your processing or low throughput, try adjusting those settings.

• Application Default Credentials (ADC) Overview
• BigQuery Introduction
• BigQuery Quotas and Limits
• BigQuery Schema Formats and Types

This plugin supports the following configuration options plus the Common options described later.

Also see Common options for a list of options supported by all output plugins.

• Value type is number
• Default value is 128

The maximum number of messages to upload at a single time. This number must be < 10,000. Batching can increase performance and throughput to a point, but at the cost of per-request latency. Too few rows per request and the overhead of each request can make ingestion inefficient. Too many rows per request and the throughput may drop. BigQuery recommends using about 500 rows per request, but experimentation with representative data (schema and data sizes) will help you determine the ideal batch size.

• Value type is number
• Default value is 1_000_000

An approximate number of bytes to upload as part of a batch. This number should be < 10MB or inserts may fail.

• Value type is string
• Default value is nil

Schema for log data. It must follow the format name1:type1(,name2:type2)*. For example, path:STRING,status:INTEGER,score:FLOAT.

• This is a required setting.
• Value type is string
• There is no default value for this setting.

The BigQuery dataset the tables for the events will be added to.

• Value type is string
• Default value is "%Y-%m-%dT%H:00"

Time pattern for BigQuery table, defaults to hourly tables. Must Time.strftime patterns: www.ruby-doc.org/core-2.0/Time.html#method-i-strftime

• Value type is number

• This is a required setting.
• Value type is string
• Default value is "/tmp/bigquery".

The location to store events that could not be uploaded due to errors. By default if any message in an insert is invalid all will fail. You can use skip_invalid_rows to allow partial inserts.

Consider using an additional Logstash input to pipe the contents of these to an alert platform so you can manually fix the events.

Or use GCS FUSE to transparently upload to a GCS bucket.

Files names follow the pattern [table name]-[UNIX timestamp].log

• Value type is number
• Default value is 5

Uploads all data this often even if other upload criteria aren’t met.

• Value type is boolean
• Default value is false

Indicates if BigQuery should ignore values that are not represented in the table schema. If true, the extra values are discarded. If false, BigQuery will reject the records with extra fields and the job will fail. The default value is false.

mutate {
    remove_field => ["@version","@timestamp","path","host","type", "message"]
}

• Value type is string
• Default value is nil

If Logstash is running within Google Compute Engine, the plugin can use GCE’s Application Default Credentials. Outside of GCE, you will need to specify a Service Account JSON key file.

• Value type is hash
• Default value is nil

Schema for log data as a hash. These can include nested records, descriptions, and modes.

Example:

json_schema => {
  fields => [{
    name => "endpoint"
    type => "STRING"
    description => "Request route"
  }, {
    name => "status"
    type => "INTEGER"
    mode => "NULLABLE"
  }, {
    name => "params"
    type => "RECORD"
    mode => "REPEATED"
    fields => [{
      name => "key"
      type => "STRING"
     }, {
      name => "value"
      type => "STRING"
    }]
  }]
}

• Value type is string

• This is a required setting.
• Value type is string
• There is no default value for this setting.

Google Cloud Project ID (number, not Project Name!).

• Value type is string

• Value type is boolean
• Default value is false

Insert all valid rows of a request, even if invalid rows exist. The default value is false, which causes the entire request to fail if any invalid rows exist.

• Value type is string
• Default value is "logstash"

BigQuery table ID prefix to be used when creating new tables for log data. Table name will be <table_prefix><table_separator><date>

• Value type is string
• Default value is "_"

BigQuery table separator to be added between the table_prefix and the date suffix.

• Value type is string

• Value type is string

• Value type is number
• Default value is 60

Uploader interval when uploading new files to BigQuery. Adjust time based on your time pattern (for example, for hourly files, this interval can be around one hour).

These configuration options are supported by all output plugins:

• Value type is codec
• Default value is "plain"

The codec used for output data. Output codecs are a convenient method for encoding your data before it leaves the output without needing a separate filter in your Logstash pipeline.

• Value type is boolean
• Default value is true

Disable or enable metric logging for this specific plugin instance. By default we record all the metrics we can, but you can disable metrics collection for a specific plugin.

• Value type is string
• There is no default value for this setting.

Add a unique ID to the plugin configuration. If no ID is specified, Logstash will generate one. It is strongly recommended to set this ID in your configuration. This is particularly useful when you have two or more plugins of the same type. For example, if you have 2 google_bigquery outputs. Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.

output {
  google_bigquery {
    id => "my_plugin_id"
  }
}