gcp_cloud_storage
This component is mostly stable but breaking changes could still be made outside of major version releases if a fundamental problem with the component is found.
Sends message parts as objects to a Google Cloud Storage bucket. Each object is uploaded with the path specified with the path
field.
Introduced in version 1.0.0.
- Common
- Advanced
# Common config fields, showing default values
output:
label: ""
gcp_cloud_storage:
bucket: "" # No default (required)
path: ${!count("files")}-${!timestamp_unix_nano()}.txt
content_type: application/octet-stream
collision_mode: overwrite
timeout: 3s
max_in_flight: 64
batching:
count: 0
byte_size: 0
period: ""
jitter: 0
check: ""
# All config fields, showing default values
output:
label: ""
gcp_cloud_storage:
bucket: "" # No default (required)
path: ${!count("files")}-${!timestamp_unix_nano()}.txt
content_type: application/octet-stream
content_encoding: ""
collision_mode: overwrite
chunk_size: 16777216
timeout: 3s
max_in_flight: 64
batching:
count: 0
byte_size: 0
period: ""
jitter: 0
check: ""
processors: [] # No default (optional)
In order to have a different path for each object you should use function interpolations described here, which are calculated per message of a batch.
Metadata
Metadata fields on messages will be sent as headers, in order to mutate these values (or remove them) check out the metadata docs.
Credentials
By default Bento will use a shared credentials file when connecting to GCP services. You can find out more in this document.
Batching
It's common to want to upload messages to Google Cloud Storage as batched archives, the easiest way to do this is to batch your messages at the output level and join the batch of messages with an archive
and/or compress
processor.
For example, if we wished to upload messages as a .tar.gz archive of documents we could achieve that with the following config:
output:
gcp_cloud_storage:
bucket: TODO
path: ${!count("files")}-${!timestamp_unix_nano()}.tar.gz
batching:
count: 100
period: 10s
processors:
- archive:
format: tar
- compress:
algorithm: gzip
Alternatively, if we wished to upload JSON documents as a single large document containing an array of objects we can do that with:
output:
gcp_cloud_storage:
bucket: TODO
path: ${!count("files")}-${!timestamp_unix_nano()}.json
batching:
count: 100
processors:
- archive:
format: json_array
Performance
This output benefits from sending multiple messages in flight in parallel for improved performance. You can tune the max number of in flight messages (or message batches) with the field max_in_flight
.
This output benefits from sending messages as a batch for improved performance. Batches can be formed at both the input and output level. You can find out more in this doc.
Fields
bucket
The bucket to upload messages to.
Type: string
path
The path of each message to upload. This field supports interpolation functions.
Type: string
Default: "${!count(\"files\")}-${!timestamp_unix_nano()}.txt"
# Examples
path: ${!count("files")}-${!timestamp_unix_nano()}.txt
path: ${!meta("kafka_key")}.json
path: ${!json("doc.namespace")}/${!json("doc.id")}.json
content_type
The content type to set for each object. This field supports interpolation functions.
Type: string
Default: "application/octet-stream"
content_encoding
An optional content encoding to set for each object. This field supports interpolation functions.
Type: string
Default: ""
collision_mode
Determines how file path collisions should be dealt with.
Type: string
Default: "overwrite"
Requires version 1.0.0 or newer
Option | Summary |
---|---|
append | Append the message bytes to the original file. |
error-if-exists | Return an error, this is the equivalent of a nack. |
ignore | Do not modify the original file, the new data will be dropped. |
overwrite | Replace the existing file with the new one. |
chunk_size
An optional chunk size which controls the maximum number of bytes of the object that the Writer will attempt to send to the server in a single request. If ChunkSize is set to zero, chunking will be disabled.
Type: int
Default: 16777216
timeout
The maximum period to wait on an upload before abandoning it and reattempting.
Type: string
Default: "3s"
# Examples
timeout: 1s
timeout: 500ms
max_in_flight
The maximum number of message batches to have in flight at a given time. Increase this to improve throughput.
Type: int
Default: 64
batching
Allows you to configure a batching policy.
Type: object
# Examples
batching:
byte_size: 5000
count: 0
period: 1s
batching:
count: 10
period: 1s
batching:
check: this.contains("END BATCH")
count: 0
period: 1m
batching:
count: 10
jitter: 0.1
period: 10s
batching.count
A number of messages at which the batch should be flushed. If 0
disables count based batching.
Type: int
Default: 0
batching.byte_size
An amount of bytes at which the batch should be flushed. If 0
disables size based batching.
Type: int
Default: 0
batching.period
A period in which an incomplete batch should be flushed regardless of its size.
Type: string
Default: ""
# Examples
period: 1s
period: 1m
period: 500ms
batching.jitter
A non-negative factor that adds random delay to batch flush intervals, where delay is determined uniformly at random between 0
and jitter * period
. For example, with period: 100ms
and jitter: 0.1
, each flush will be delayed by a random duration between 0-10ms
.
Type: float
Default: 0
# Examples
jitter: 0.01
jitter: 0.1
jitter: 1
batching.check
A Bloblang query that should return a boolean value indicating whether a message should end a batch.
Type: string
Default: ""
# Examples
check: this.type == "end_of_transaction"
batching.processors
A list of processors to apply to a batch as it is flushed. This allows you to aggregate and archive the batch however you see fit. Please note that all resulting messages are flushed as a single batch, therefore splitting the batch into smaller batches using these processors is a no-op.
Type: array
# Examples
processors:
- archive:
format: concatenate
processors:
- archive:
format: lines
processors:
- archive:
format: json_array