Retrieve a pipeline.

Retrieve a pipeline.

Path Parameters
pipeline_name string — REQUIRED Unique pipeline name

Responses
200 Pipeline retrieved successfully 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.
404 Pipeline with that name does not exist 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.