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Fully update a pipeline if it already exists, otherwise create a new pipeline.

Fully update a pipeline if it already exists, otherwise create a new pipeline.

Path Parameters
pipeline_name string — REQUIRED

Unique pipeline name

Request Body — REQUIRED
description string — REQUIRED

Pipeline description.

name string — REQUIRED

Pipeline name.

program_code string — REQUIRED

Program SQL code.

program_config object — REQUIRED

Program configuration.

profile string

Possible values: [dev, unoptimized, optimized]

Enumeration of possible compilation profiles that can be passed to the Rust compiler as an argument via cargo build --profile <>. A compilation profile affects among other things the compilation speed (how long till the program is ready to be run) and runtime speed (the performance while running).

runtime_config object — REQUIRED

Global pipeline configuration settings. This is the publicly exposed type for users to configure pipelines.

clock_resolution_usecs int64

Real-time clock resolution in microseconds.

This parameter controls the execution of queries that use the NOW() function. The output of such queries depends on the real-time clock and can change over time without any external inputs. The pipeline will update the clock value and trigger incremental recomputation at most each clock_resolution_usecs microseconds.

It is set to 100 milliseconds (100,000 microseconds) by default.

Set to null to disable periodic clock updates.

cpu_profiler boolean

Enable CPU profiler.

The default value is true.

fault_tolerance string

Possible values: [initial_state, latest_checkpoint]

Fault-tolerance configuration for runtime startup.

max_buffering_delay_usecs int64

Maximal delay in microseconds to wait for min_batch_size_records to get buffered by the controller, defaults to 0.

min_batch_size_records int64

Minimal input batch size.

The controller delays pushing input records to the circuit until at least min_batch_size_records records have been received (total across all endpoints) or max_buffering_delay_usecs microseconds have passed since at least one input records has been buffered. Defaults to 0.

min_storage_bytes integer

The minimum estimated number of bytes in a batch of data to write it to storage. This is provided for debugging and fine-tuning and should ordinarily be left unset. It only has an effect when storage is set to true.

A value of 0 will write even empty batches to storage, and nonzero values provide a threshold. usize::MAX would effectively disable storage.

resources object
cpu_cores_max int64

The maximum number of CPU cores to reserve for an instance of this pipeline

cpu_cores_min int64

The minimum number of CPU cores to reserve for an instance of this pipeline

memory_mb_max int64

The maximum memory in Megabytes to reserve for an instance of this pipeline

memory_mb_min int64

The minimum memory in Megabytes to reserve for an instance of this pipeline

storage_class string

Storage class to use for an instance of this pipeline. The class determines storage performance such as IOPS and throughput.

storage_mb_max int64

The total storage in Megabytes to reserve for an instance of this pipeline

storage boolean

Should storage be enabled for this pipeline?

  • If false (default), the pipeline's state is kept in in-memory data-structures. This is useful if the pipeline's state will fit in memory and if the pipeline is ephemeral and does not need to be recovered after a restart. The pipeline will most likely run faster since it does not need to access storage.

  • If true, the pipeline's state is kept on storage. This allows the pipeline to work with state that will not fit into memory. It also allows the state to be checkpointed and recovered across restarts. This feature is currently experimental.

tracing boolean

Enable pipeline tracing.

tracing_endpoint_jaeger string

Jaeger tracing endpoint to send tracing information to.

workers int32

Number of DBSP worker threads.

udf_rust string

Rust code for UDFs.

udf_toml string

Rust dependencies in the TOML format.

Responses
200

Pipeline successfully updated

Schema — OPTIONAL
created_at date-time

Timestamp when the pipeline was originally created.

deployment_config object — OPTIONAL

Pipeline deployment configuration. It represents configuration entries directly provided by the user (e.g., runtime configuration) and entries derived from the schema of the compiled program (e.g., connectors). Storage configuration, if applicable, is set by the runner.

clock_resolution_usecs int64 — OPTIONAL

Real-time clock resolution in microseconds.

This parameter controls the execution of queries that use the NOW() function. The output of such queries depends on the real-time clock and can change over time without any external inputs. The pipeline will update the clock value and trigger incremental recomputation at most each clock_resolution_usecs microseconds.

It is set to 100 milliseconds (100,000 microseconds) by default.

Set to null to disable periodic clock updates.

cpu_profiler boolean — OPTIONAL

Enable CPU profiler.

The default value is true.

fault_tolerance string — OPTIONAL

Possible values: [initial_state, latest_checkpoint]

Fault-tolerance configuration for runtime startup.

max_buffering_delay_usecs int64 — OPTIONAL

Maximal delay in microseconds to wait for min_batch_size_records to get buffered by the controller, defaults to 0.

min_batch_size_records int64 — OPTIONAL

Minimal input batch size.

The controller delays pushing input records to the circuit until at least min_batch_size_records records have been received (total across all endpoints) or max_buffering_delay_usecs microseconds have passed since at least one input records has been buffered. Defaults to 0.

min_storage_bytes integer — OPTIONAL

The minimum estimated number of bytes in a batch of data to write it to storage. This is provided for debugging and fine-tuning and should ordinarily be left unset. It only has an effect when storage is set to true.

A value of 0 will write even empty batches to storage, and nonzero values provide a threshold. usize::MAX would effectively disable storage.

resources object — OPTIONAL
cpu_cores_max int64 — OPTIONAL

The maximum number of CPU cores to reserve for an instance of this pipeline

cpu_cores_min int64 — OPTIONAL

The minimum number of CPU cores to reserve for an instance of this pipeline

memory_mb_max int64 — OPTIONAL

The maximum memory in Megabytes to reserve for an instance of this pipeline

memory_mb_min int64 — OPTIONAL

The minimum memory in Megabytes to reserve for an instance of this pipeline

storage_class string — OPTIONAL

Storage class to use for an instance of this pipeline. The class determines storage performance such as IOPS and throughput.

storage_mb_max int64 — OPTIONAL

The total storage in Megabytes to reserve for an instance of this pipeline

storage boolean — OPTIONAL

Should storage be enabled for this pipeline?

  • If false (default), the pipeline's state is kept in in-memory data-structures. This is useful if the pipeline's state will fit in memory and if the pipeline is ephemeral and does not need to be recovered after a restart. The pipeline will most likely run faster since it does not need to access storage.

  • If true, the pipeline's state is kept on storage. This allows the pipeline to work with state that will not fit into memory. It also allows the state to be checkpointed and recovered across restarts. This feature is currently experimental.

tracing boolean — OPTIONAL

Enable pipeline tracing.

tracing_endpoint_jaeger string — OPTIONAL

Jaeger tracing endpoint to send tracing information to.

workers int32 — OPTIONAL

Number of DBSP worker threads.

inputs object

Input endpoint configuration.

name string — OPTIONAL

Pipeline name.

outputs object — OPTIONAL

Output endpoint configuration.

storage_config object — OPTIONAL

Configuration for persistent storage in a [PipelineConfig].

cache string — OPTIONAL

Possible values: [page_cache, feldera_cache]

How to cache access to storage within a Feldera pipeline.

path string

The location where the pipeline state is stored or will be stored.

It should point to a path on the file-system of the machine/container where the pipeline will run. If that path doesn't exist yet, or if it does not contain any checkpoints, then the pipeline creates it and starts from an initial state in which no data has yet been received. If it does exist, then the pipeline starts from the most recent checkpoint that already exists there. In either case, (further) checkpoints will be written there.

deployment_desired_status string

Possible values: [Shutdown, Paused, Running]

deployment_error object — OPTIONAL

Information returned by REST API endpoints on error.

details object

Detailed error metadata. The contents of this field is determined by error_code.

error_code string

Error code is a string that specifies this error type.

message string

Human-readable error message.

deployment_location string — OPTIONAL

Location where the pipeline can be reached at runtime (e.g., a TCP port number or a URI).

deployment_status string

Possible values: [Shutdown, Provisioning, Initializing, Paused, Running, Unavailable, Failed, ShuttingDown]

Pipeline status.

This type represents the state of the pipeline tracked by the pipeline runner and observed by the API client via the GET /v0/pipelines/{name} endpoint.

The lifecycle of a pipeline​

The following automaton captures the lifecycle of the pipeline. Individual states and transitions of the automaton are described below.

  • States labeled with the hourglass symbol (⌛) are timed states. The automaton stays in timed state until the corresponding operation completes or until it transitions to become failed after the pre-defined timeout period expires.

  • State transitions labeled with API endpoint names (/start, /pause, /shutdown) are triggered by invoking corresponding endpoint, e.g., POST /v0/pipelines/{name}/start. Note that these only express desired state, and are applied asynchronously by the automata.

Shutdown◄────────────────────┐
│                        │
/start or /pause│                    ShuttingDown ◄────── Failed
│                        ▲                  ▲
▼              /shutdown │                  │
⌛Provisioning ──────────────────┤        Shutdown, Provisioning,
│                        │        Initializing, Paused,
│                        │         Running, Unavailable
▼                        │    (all states except ShuttingDown
⌛Initializing ──────────────────┤      can transition to Failed)
│                        │
┌─────────┼────────────────────────┴─┐
│         ▼                          │
│       Paused  ◄──────► Unavailable │
│       │    ▲                ▲      │
│ /start│    │/pause          │      │
│       ▼    │                │      │
│      Running ◄──────────────┘      │
└────────────────────────────────────┘

Desired and actual status​

We use the desired state model to manage the lifecycle of a pipeline. In this model, the pipeline has two status attributes associated with it at runtime: the desired status, which represents what the user would like the pipeline to do, and the current status, which represents the actual state of the pipeline. The pipeline runner service continuously monitors both fields and steers the pipeline towards the desired state specified by the user. Only three of the states in the pipeline automaton above can be used as desired statuses: Paused, Running, and Shutdown. These statuses are selected by invoking REST endpoints shown in the diagram.

The user can monitor the current state of the pipeline via the GET /v0/pipelines/{name} endpoint, which returns an object of type ExtendedPipelineDescr. In a typical scenario, the user first sets the desired state, e.g., by invoking the /start endpoint, and then polls the GET /v0/pipelines/{name} endpoint to monitor the actual status of the pipeline until its deployment_status attribute changes to "running" indicating that the pipeline has been successfully initialized and is processing data, or "failed", indicating an error.

deployment_status_since date-time

Time when the pipeline was assigned its current status of the pipeline.

description string

Pipeline description.

id uuid

Pipeline identifier.

name string

Pipeline name.

program_binary_url string — OPTIONAL

URL where to download the program binary from.

program_code string

Program SQL code.

program_config object

Program configuration.

profile string — OPTIONAL

Possible values: [dev, unoptimized, optimized]

Enumeration of possible compilation profiles that can be passed to the Rust compiler as an argument via cargo build --profile <>. A compilation profile affects among other things the compilation speed (how long till the program is ready to be run) and runtime speed (the performance while running).

program_info object — OPTIONAL

Program information generated by the SQL compiler which includes schema, input connectors and output connectors.

input_connectors object

Input connectors derived from the schema.

output_connectors object

Output connectors derived from the schema.

schema object

A struct containing the tables (inputs) and views for a program.

Parse from the JSON data-type of the DDL generated by the SQL compiler.

inputs object[]
case_sensitive boolean
name string
fields object[]
case_sensitive boolean
name string
columntype (circular)
materialized boolean — OPTIONAL
properties object — OPTIONAL
outputs object[]
case_sensitive boolean
name string
fields object[]
case_sensitive boolean
name string
columntype (circular)
materialized boolean — OPTIONAL
properties object — OPTIONAL
udf_stubs string — OPTIONAL

UDF stubs.

program_status

Program compilation status.

program_status_since date-time

Timestamp when the current program status was set.

program_version int64

Version number.

runtime_config object

Global pipeline configuration settings. This is the publicly exposed type for users to configure pipelines.

clock_resolution_usecs int64 — OPTIONAL

Real-time clock resolution in microseconds.

This parameter controls the execution of queries that use the NOW() function. The output of such queries depends on the real-time clock and can change over time without any external inputs. The pipeline will update the clock value and trigger incremental recomputation at most each clock_resolution_usecs microseconds.

It is set to 100 milliseconds (100,000 microseconds) by default.

Set to null to disable periodic clock updates.

cpu_profiler boolean — OPTIONAL

Enable CPU profiler.

The default value is true.

fault_tolerance string — OPTIONAL

Possible values: [initial_state, latest_checkpoint]

Fault-tolerance configuration for runtime startup.

max_buffering_delay_usecs int64 — OPTIONAL

Maximal delay in microseconds to wait for min_batch_size_records to get buffered by the controller, defaults to 0.

min_batch_size_records int64 — OPTIONAL

Minimal input batch size.

The controller delays pushing input records to the circuit until at least min_batch_size_records records have been received (total across all endpoints) or max_buffering_delay_usecs microseconds have passed since at least one input records has been buffered. Defaults to 0.

min_storage_bytes integer — OPTIONAL

The minimum estimated number of bytes in a batch of data to write it to storage. This is provided for debugging and fine-tuning and should ordinarily be left unset. It only has an effect when storage is set to true.

A value of 0 will write even empty batches to storage, and nonzero values provide a threshold. usize::MAX would effectively disable storage.

resources object — OPTIONAL
cpu_cores_max int64 — OPTIONAL

The maximum number of CPU cores to reserve for an instance of this pipeline

cpu_cores_min int64 — OPTIONAL

The minimum number of CPU cores to reserve for an instance of this pipeline

memory_mb_max int64 — OPTIONAL

The maximum memory in Megabytes to reserve for an instance of this pipeline

memory_mb_min int64 — OPTIONAL

The minimum memory in Megabytes to reserve for an instance of this pipeline

storage_class string — OPTIONAL

Storage class to use for an instance of this pipeline. The class determines storage performance such as IOPS and throughput.

storage_mb_max int64 — OPTIONAL

The total storage in Megabytes to reserve for an instance of this pipeline

storage boolean — OPTIONAL

Should storage be enabled for this pipeline?

  • If false (default), the pipeline's state is kept in in-memory data-structures. This is useful if the pipeline's state will fit in memory and if the pipeline is ephemeral and does not need to be recovered after a restart. The pipeline will most likely run faster since it does not need to access storage.

  • If true, the pipeline's state is kept on storage. This allows the pipeline to work with state that will not fit into memory. It also allows the state to be checkpointed and recovered across restarts. This feature is currently experimental.

tracing boolean — OPTIONAL

Enable pipeline tracing.

tracing_endpoint_jaeger string — OPTIONAL

Jaeger tracing endpoint to send tracing information to.

workers int32 — OPTIONAL

Number of DBSP worker threads.

udf_rust string

Rust code for UDFs.

udf_toml string

Rust dependencies in the TOML format.

version int64

Version number.

201

Pipeline successfully created

Schema — OPTIONAL
created_at date-time

Timestamp when the pipeline was originally created.

deployment_config object — OPTIONAL

Pipeline deployment configuration. It represents configuration entries directly provided by the user (e.g., runtime configuration) and entries derived from the schema of the compiled program (e.g., connectors). Storage configuration, if applicable, is set by the runner.

clock_resolution_usecs int64 — OPTIONAL

Real-time clock resolution in microseconds.

This parameter controls the execution of queries that use the NOW() function. The output of such queries depends on the real-time clock and can change over time without any external inputs. The pipeline will update the clock value and trigger incremental recomputation at most each clock_resolution_usecs microseconds.

It is set to 100 milliseconds (100,000 microseconds) by default.

Set to null to disable periodic clock updates.

cpu_profiler boolean — OPTIONAL

Enable CPU profiler.

The default value is true.

fault_tolerance string — OPTIONAL

Possible values: [initial_state, latest_checkpoint]

Fault-tolerance configuration for runtime startup.

max_buffering_delay_usecs int64 — OPTIONAL

Maximal delay in microseconds to wait for min_batch_size_records to get buffered by the controller, defaults to 0.

min_batch_size_records int64 — OPTIONAL

Minimal input batch size.

The controller delays pushing input records to the circuit until at least min_batch_size_records records have been received (total across all endpoints) or max_buffering_delay_usecs microseconds have passed since at least one input records has been buffered. Defaults to 0.

min_storage_bytes integer — OPTIONAL

The minimum estimated number of bytes in a batch of data to write it to storage. This is provided for debugging and fine-tuning and should ordinarily be left unset. It only has an effect when storage is set to true.

A value of 0 will write even empty batches to storage, and nonzero values provide a threshold. usize::MAX would effectively disable storage.

resources object — OPTIONAL
cpu_cores_max int64 — OPTIONAL

The maximum number of CPU cores to reserve for an instance of this pipeline

cpu_cores_min int64 — OPTIONAL

The minimum number of CPU cores to reserve for an instance of this pipeline

memory_mb_max int64 — OPTIONAL

The maximum memory in Megabytes to reserve for an instance of this pipeline

memory_mb_min int64 — OPTIONAL

The minimum memory in Megabytes to reserve for an instance of this pipeline

storage_class string — OPTIONAL

Storage class to use for an instance of this pipeline. The class determines storage performance such as IOPS and throughput.

storage_mb_max int64 — OPTIONAL

The total storage in Megabytes to reserve for an instance of this pipeline

storage boolean — OPTIONAL

Should storage be enabled for this pipeline?

  • If false (default), the pipeline's state is kept in in-memory data-structures. This is useful if the pipeline's state will fit in memory and if the pipeline is ephemeral and does not need to be recovered after a restart. The pipeline will most likely run faster since it does not need to access storage.

  • If true, the pipeline's state is kept on storage. This allows the pipeline to work with state that will not fit into memory. It also allows the state to be checkpointed and recovered across restarts. This feature is currently experimental.

tracing boolean — OPTIONAL

Enable pipeline tracing.

tracing_endpoint_jaeger string — OPTIONAL

Jaeger tracing endpoint to send tracing information to.

workers int32 — OPTIONAL

Number of DBSP worker threads.

inputs object

Input endpoint configuration.

name string — OPTIONAL

Pipeline name.

outputs object — OPTIONAL

Output endpoint configuration.

storage_config object — OPTIONAL

Configuration for persistent storage in a [PipelineConfig].

cache string — OPTIONAL

Possible values: [page_cache, feldera_cache]

How to cache access to storage within a Feldera pipeline.

path string

The location where the pipeline state is stored or will be stored.

It should point to a path on the file-system of the machine/container where the pipeline will run. If that path doesn't exist yet, or if it does not contain any checkpoints, then the pipeline creates it and starts from an initial state in which no data has yet been received. If it does exist, then the pipeline starts from the most recent checkpoint that already exists there. In either case, (further) checkpoints will be written there.

deployment_desired_status string

Possible values: [Shutdown, Paused, Running]

deployment_error object — OPTIONAL

Information returned by REST API endpoints on error.

details object

Detailed error metadata. The contents of this field is determined by error_code.

error_code string

Error code is a string that specifies this error type.

message string

Human-readable error message.

deployment_location string — OPTIONAL

Location where the pipeline can be reached at runtime (e.g., a TCP port number or a URI).

deployment_status string

Possible values: [Shutdown, Provisioning, Initializing, Paused, Running, Unavailable, Failed, ShuttingDown]

Pipeline status.

This type represents the state of the pipeline tracked by the pipeline runner and observed by the API client via the GET /v0/pipelines/{name} endpoint.

The lifecycle of a pipeline​

The following automaton captures the lifecycle of the pipeline. Individual states and transitions of the automaton are described below.

  • States labeled with the hourglass symbol (⌛) are timed states. The automaton stays in timed state until the corresponding operation completes or until it transitions to become failed after the pre-defined timeout period expires.

  • State transitions labeled with API endpoint names (/start, /pause, /shutdown) are triggered by invoking corresponding endpoint, e.g., POST /v0/pipelines/{name}/start. Note that these only express desired state, and are applied asynchronously by the automata.

Shutdown◄────────────────────┐
│                        │
/start or /pause│                    ShuttingDown ◄────── Failed
│                        ▲                  ▲
▼              /shutdown │                  │
⌛Provisioning ──────────────────┤        Shutdown, Provisioning,
│                        │        Initializing, Paused,
│                        │         Running, Unavailable
▼                        │    (all states except ShuttingDown
⌛Initializing ──────────────────┤      can transition to Failed)
│                        │
┌─────────┼────────────────────────┴─┐
│         ▼                          │
│       Paused  ◄──────► Unavailable │
│       │    ▲                ▲      │
│ /start│    │/pause          │      │
│       ▼    │                │      │
│      Running ◄──────────────┘      │
└────────────────────────────────────┘

Desired and actual status​

We use the desired state model to manage the lifecycle of a pipeline. In this model, the pipeline has two status attributes associated with it at runtime: the desired status, which represents what the user would like the pipeline to do, and the current status, which represents the actual state of the pipeline. The pipeline runner service continuously monitors both fields and steers the pipeline towards the desired state specified by the user. Only three of the states in the pipeline automaton above can be used as desired statuses: Paused, Running, and Shutdown. These statuses are selected by invoking REST endpoints shown in the diagram.

The user can monitor the current state of the pipeline via the GET /v0/pipelines/{name} endpoint, which returns an object of type ExtendedPipelineDescr. In a typical scenario, the user first sets the desired state, e.g., by invoking the /start endpoint, and then polls the GET /v0/pipelines/{name} endpoint to monitor the actual status of the pipeline until its deployment_status attribute changes to "running" indicating that the pipeline has been successfully initialized and is processing data, or "failed", indicating an error.

deployment_status_since date-time

Time when the pipeline was assigned its current status of the pipeline.

description string

Pipeline description.

id uuid

Pipeline identifier.

name string

Pipeline name.

program_binary_url string — OPTIONAL

URL where to download the program binary from.

program_code string

Program SQL code.

program_config object

Program configuration.

profile string — OPTIONAL

Possible values: [dev, unoptimized, optimized]

Enumeration of possible compilation profiles that can be passed to the Rust compiler as an argument via cargo build --profile <>. A compilation profile affects among other things the compilation speed (how long till the program is ready to be run) and runtime speed (the performance while running).

program_info object — OPTIONAL

Program information generated by the SQL compiler which includes schema, input connectors and output connectors.

input_connectors object

Input connectors derived from the schema.

output_connectors object

Output connectors derived from the schema.

schema object

A struct containing the tables (inputs) and views for a program.

Parse from the JSON data-type of the DDL generated by the SQL compiler.

inputs object[]
case_sensitive boolean
name string
fields object[]
case_sensitive boolean
name string
columntype (circular)
materialized boolean — OPTIONAL
properties object — OPTIONAL
outputs object[]
case_sensitive boolean
name string
fields object[]
case_sensitive boolean
name string
columntype (circular)
materialized boolean — OPTIONAL
properties object — OPTIONAL
udf_stubs string — OPTIONAL

UDF stubs.

program_status

Program compilation status.

program_status_since date-time

Timestamp when the current program status was set.

program_version int64

Version number.

runtime_config object

Global pipeline configuration settings. This is the publicly exposed type for users to configure pipelines.

clock_resolution_usecs int64 — OPTIONAL

Real-time clock resolution in microseconds.

This parameter controls the execution of queries that use the NOW() function. The output of such queries depends on the real-time clock and can change over time without any external inputs. The pipeline will update the clock value and trigger incremental recomputation at most each clock_resolution_usecs microseconds.

It is set to 100 milliseconds (100,000 microseconds) by default.

Set to null to disable periodic clock updates.

cpu_profiler boolean — OPTIONAL

Enable CPU profiler.

The default value is true.

fault_tolerance string — OPTIONAL

Possible values: [initial_state, latest_checkpoint]

Fault-tolerance configuration for runtime startup.

max_buffering_delay_usecs int64 — OPTIONAL

Maximal delay in microseconds to wait for min_batch_size_records to get buffered by the controller, defaults to 0.

min_batch_size_records int64 — OPTIONAL

Minimal input batch size.

The controller delays pushing input records to the circuit until at least min_batch_size_records records have been received (total across all endpoints) or max_buffering_delay_usecs microseconds have passed since at least one input records has been buffered. Defaults to 0.

min_storage_bytes integer — OPTIONAL

The minimum estimated number of bytes in a batch of data to write it to storage. This is provided for debugging and fine-tuning and should ordinarily be left unset. It only has an effect when storage is set to true.

A value of 0 will write even empty batches to storage, and nonzero values provide a threshold. usize::MAX would effectively disable storage.

resources object — OPTIONAL
cpu_cores_max int64 — OPTIONAL

The maximum number of CPU cores to reserve for an instance of this pipeline

cpu_cores_min int64 — OPTIONAL

The minimum number of CPU cores to reserve for an instance of this pipeline

memory_mb_max int64 — OPTIONAL

The maximum memory in Megabytes to reserve for an instance of this pipeline

memory_mb_min int64 — OPTIONAL

The minimum memory in Megabytes to reserve for an instance of this pipeline

storage_class string — OPTIONAL

Storage class to use for an instance of this pipeline. The class determines storage performance such as IOPS and throughput.

storage_mb_max int64 — OPTIONAL

The total storage in Megabytes to reserve for an instance of this pipeline

storage boolean — OPTIONAL

Should storage be enabled for this pipeline?

  • If false (default), the pipeline's state is kept in in-memory data-structures. This is useful if the pipeline's state will fit in memory and if the pipeline is ephemeral and does not need to be recovered after a restart. The pipeline will most likely run faster since it does not need to access storage.

  • If true, the pipeline's state is kept on storage. This allows the pipeline to work with state that will not fit into memory. It also allows the state to be checkpointed and recovered across restarts. This feature is currently experimental.

tracing boolean — OPTIONAL

Enable pipeline tracing.

tracing_endpoint_jaeger string — OPTIONAL

Jaeger tracing endpoint to send tracing information to.

workers int32 — OPTIONAL

Number of DBSP worker threads.

udf_rust string

Rust code for UDFs.

udf_toml string

Rust dependencies in the TOML format.

version int64

Version number.

400

Pipeline needs to be shutdown to be modified

Schema — OPTIONAL
details object

Detailed error metadata. The contents of this field is determined by error_code.

error_code string

Error code is a string that specifies this error type.

message string

Human-readable error message.

409

Cannot rename pipeline as the name already exists

Schema — OPTIONAL
details object

Detailed error metadata. The contents of this field is determined by error_code.

error_code string

Error code is a string that specifies this error type.

message string

Human-readable error message.