com.coxautodata.waimak.dataflow.spark
SimpleSparkDataFlow
Related Docs:
object SimpleSparkDataFlow
| package spark
com.coxautodata.waimak.dataflow.spark
Actions to execute, these will be scheduled when inputs become available.
Actions to execute, these will be scheduled when inputs become available. Executed actions must be removed from the sate.
Creates new state of the dataflow by adding an action to it.
Creates new state of the dataflow by adding an action to it.
- action to add
- new state with action
DataFlowException when:
1) at least one of the input labels is not present in the inputs
2) at least one of the input labels is not present in the outputs of existing actions
Creates new state of the dataflow by adding an input.
Creates new state of the dataflow by adding an input. Duplicate labels are handled in prepareForExecution()
- name of the input
- values of the input
- new state with the input
Creates new state of the data flow by replacing the action that is intercepted with action that intercepts it.
Creates new state of the data flow by replacing the action that is intercepted with action that intercepts it. The action to replace will differ from the intercepted action in the InterceptorAction in the case of replacing an existing InterceptorAction
All new states of the dataflow must be created via this factory method.
All new states of the dataflow must be created via this factory method. This will allow specific dataflows to pass their specific context objects into new state.
- input entities for the next state
- actions for the next state
- new instance of the implementing class
Creates new state of the dataflow by removing executed action from the actions list and adds its outputs to the inputs.
Creates new state of the dataflow by removing executed action from the actions list and adds its outputs to the inputs.
- executed actions
- outputs of the executed action
- next stage data flow without the executed action, but with its outpus as inputs
DataFlowException if number of provided outputs is not equal to the number of output labels of the action
Guids are unique, find action by guid
Guids are unique, find action by guid
Output labels are unique.
Output labels are unique. Finds action that produces outputLabel.
Inputs that were explicitly set or produced by previous actions, these are inputs for all following actions.
Inputs that were explicitly set or produced by previous actions, these are inputs for all following actions. Inputs are preserved in the data flow state, even if they are no longer required by the remaining actions. //TODO: explore the option of removing the inputs that are no longer required by remaining actions!!!
Flow DAG is valid iff: 1.
Flow DAG is valid iff: 1. All output labels and existing input labels unique 2. Each action depends on labels that are produced by actions or already present in inputs 3. Active tags is empty 4. Active dependencies is zero 5. No cyclic dependencies in labels 6. No cyclic dependencies in tags 7. No cyclic dependencies in label tag combination
Transforms the current dataflow by applying a function to it.
Transforms the current dataflow by applying a function to it.
A function that transforms a dataflow object
New dataflow
Optionally transform a dataflow depending on the output of the applying function.
Optionally transform a dataflow depending on the output of the applying function. If the transforming function returns a None then the original dataflow is returned.
A function that returns an Option[DataFlow]
DataFlow object that may have been transformed
Returns actions that are ready to run: 1.
Returns actions that are ready to run: 1. have no input labels; 2. whose inputs have been created 3. all actions whose dependent tags have been run
will not include actions that are skipped.
A function called just before the flow is executed.
A function called just before the flow is executed. By default, this function has just checks the tagging state of the flow, and could be overloaded to have implementation specific preparation steps. An overloaded function should call this function first. It would be responsible for preparing an execution environment such as cleaning temporary directories.
Execution of the flow is lazy, but registration of the datasets as sql tables can only happen when data set is created.
Execution of the flow is lazy, but registration of the datasets as sql tables can only happen when data set is created. With multiple threads consuming same table, registration of the data set as an sql table needs to happen in synchronised code.
Labels that need to be registered as temp spark views before the execution starts. This is necessary if they are to be reused by multiple parallel threads.
Tag all actions added during the taggedFlow lambda function with any given number of tags.
Tag all actions added during the taggedFlow lambda function with any given number of tags. These tags can then be used by the tagDependency() action to create a dependency in the running order of actions by tag.
Tags to apply to added actions
An intermediate flow that actions can be added to that will be be marked with the tag
Mark all actions added during the tagDependentFlow lambda function as having a dependency on the tags provided.
Mark all actions added during the tagDependentFlow lambda function as having a dependency on the tags provided. These actions will only be run once all tagged actions have finished.
Tags to create a dependency on
An intermediate flow that actions can be added to that will depended on tagged actions to have completed before running
Folder into which the temp data will be saved before commit into the output storage: folders, RDBMs, Key Value tables.
Folder into which the temp data will be saved before commit into the output storage: folders, RDBMs, Key Value tables.
Created by Alexei Perelighin on 22/12/17.