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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
name string — REQUIRED
program_code string — REQUIRED
program_config object

Program configuration.

cache boolean

If true (default), when a prior compilation with the same checksum already exists, the output of that (i.e., binary) is used. Set false to always trigger a new compilation, which might take longer and as well can result in overriding an existing binary.

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

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 object

Fault-tolerance configuration for runtime startup.

checkpoint_interval_secs int64

Interval between automatic checkpoints, in seconds.

The default is 60 seconds. A value of 0 disables automatic checkpointing.

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.

pin_cpus integer[]

Optionally, a list of CPU numbers for CPUs to which the pipeline may pin its worker threads. Specify at least twice as many CPU numbers as workers. CPUs are generally numbered starting from 0. The pipeline might not be able to honor CPU pinning requests.

CPU pinning can make pipelines run faster and perform more consistently, as long as different pipelines running on the same machine are pinned to different CPUs.

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 object

Storage configuration for a pipeline.

backend

Backend storage configuration.

cache_mib integer

The maximum size of the in-memory storage cache, in mebibytes.

The default is 256 MiB, times the number of workers.

compression string

Possible values: [default, none, snappy]

Storage compression algorithm.

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.

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

The default is 1,048,576 (1 MiB).

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
udf_toml string
Responses
200

Pipeline successfully updated

Schema — OPTIONAL
created_at date-time
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_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. 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
description string
id uuid

Pipeline identifier.

name string
platform_version string
program_code string
program_config object

Program configuration.

cache boolean — OPTIONAL

If true (default), when a prior compilation with the same checksum already exists, the output of that (i.e., binary) is used. Set false to always trigger a new compilation, which might take longer and as well can result in overriding an existing binary.

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 is the result of the SQL compilation.

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

Generated user defined function (UDF) stubs Rust code: stubs.rs

program_status

Program compilation status.

program_status_since date-time
program_version int64

Version number.

refresh_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 object — OPTIONAL

Fault-tolerance configuration for runtime startup.

checkpoint_interval_secs int64 — OPTIONAL

Interval between automatic checkpoints, in seconds.

The default is 60 seconds. A value of 0 disables automatic checkpointing.

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.

pin_cpus integer[] — OPTIONAL

Optionally, a list of CPU numbers for CPUs to which the pipeline may pin its worker threads. Specify at least twice as many CPU numbers as workers. CPUs are generally numbered starting from 0. The pipeline might not be able to honor CPU pinning requests.

CPU pinning can make pipelines run faster and perform more consistently, as long as different pipelines running on the same machine are pinned to different CPUs.

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 object — OPTIONAL

Storage configuration for a pipeline.

backend — OPTIONAL

Backend storage configuration.

cache_mib integer — OPTIONAL

The maximum size of the in-memory storage cache, in mebibytes.

The default is 256 MiB, times the number of workers.

compression string — OPTIONAL

Possible values: [default, none, snappy]

Storage compression algorithm.

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.

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

The default is 1,048,576 (1 MiB).

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
udf_toml string
version int64

Version number.

201

Pipeline successfully created

Schema — OPTIONAL
created_at date-time
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_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. 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
description string
id uuid

Pipeline identifier.

name string
platform_version string
program_code string
program_config object

Program configuration.

cache boolean — OPTIONAL

If true (default), when a prior compilation with the same checksum already exists, the output of that (i.e., binary) is used. Set false to always trigger a new compilation, which might take longer and as well can result in overriding an existing binary.

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 is the result of the SQL compilation.

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

Generated user defined function (UDF) stubs Rust code: stubs.rs

program_status

Program compilation status.

program_status_since date-time
program_version int64

Version number.

refresh_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 object — OPTIONAL

Fault-tolerance configuration for runtime startup.

checkpoint_interval_secs int64 — OPTIONAL

Interval between automatic checkpoints, in seconds.

The default is 60 seconds. A value of 0 disables automatic checkpointing.

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.

pin_cpus integer[] — OPTIONAL

Optionally, a list of CPU numbers for CPUs to which the pipeline may pin its worker threads. Specify at least twice as many CPU numbers as workers. CPUs are generally numbered starting from 0. The pipeline might not be able to honor CPU pinning requests.

CPU pinning can make pipelines run faster and perform more consistently, as long as different pipelines running on the same machine are pinned to different CPUs.

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 object — OPTIONAL

Storage configuration for a pipeline.

backend — OPTIONAL

Backend storage configuration.

cache_mib integer — OPTIONAL

The maximum size of the in-memory storage cache, in mebibytes.

The default is 256 MiB, times the number of workers.

compression string — OPTIONAL

Possible values: [default, none, snappy]

Storage compression algorithm.

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.

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

The default is 1,048,576 (1 MiB).

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
udf_toml string
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.