@Internal public class StreamGraphGenerator extends Object
StreamGraph
from a graph of Transformation
s.
This traverses the tree of Transformations
starting from the sinks. At each
transformation we recursively transform the inputs, then create a node in the StreamGraph
and add edges from the input Nodes to our newly created node. The transformation methods return
the IDs of the nodes in the StreamGraph that represent the input transformation. Several IDs can
be returned to be able to deal with feedback transformations and unions.
Partitioning, split/select and union don't create actual nodes in the StreamGraph
. For
these, we create a virtual node in the StreamGraph
that holds the specific property, i.e.
partitioning, selector and so on. When an edge is created from a virtual node to a downstream
node the StreamGraph
resolved the id of the original node and creates an edge in the
graph with the desired property. For example, if you have this graph:
Map-1 -> HashPartition-2 -> Map-3
where the numbers represent transformation IDs. We first recurse all the way down. Map-1
is transformed, i.e. we create a StreamNode
with ID 1. Then we transform the
HashPartition
, for this, we create virtual node of ID 4 that holds the property HashPartition
. This transformation returns the ID 4. Then we transform the Map-3
. We add
the edge 4 -> 3
. The StreamGraph
resolved the actual node with ID 1 and creates
and edge 1 -> 3
with the property HashPartition.
Modifier and Type | Field and Description |
---|---|
static String |
DEFAULT_BATCH_JOB_NAME |
static int |
DEFAULT_LOWER_BOUND_MAX_PARALLELISM |
static String |
DEFAULT_SLOT_SHARING_GROUP |
static String |
DEFAULT_STREAMING_JOB_NAME |
static TimeCharacteristic |
DEFAULT_TIME_CHARACTERISTIC |
protected static Integer |
iterationIdCounter |
Constructor and Description |
---|
StreamGraphGenerator(List<Transformation<?>> transformations,
ExecutionConfig executionConfig,
CheckpointConfig checkpointConfig) |
StreamGraphGenerator(List<Transformation<?>> transformations,
ExecutionConfig executionConfig,
CheckpointConfig checkpointConfig,
Configuration configuration) |
Modifier and Type | Method and Description |
---|---|
StreamGraph |
generate() |
static int |
getNewIterationNodeId() |
void |
setSavepointRestoreSettings(SavepointRestoreSettings savepointRestoreSettings) |
StreamGraphGenerator |
setSlotSharingGroupResource(Map<String,ResourceProfile> slotSharingGroupResources)
Specify fine-grained resource requirements for slot sharing groups.
|
StreamGraphGenerator |
setStateBackend(StateBackend stateBackend) |
StreamGraphGenerator |
setTimeCharacteristic(TimeCharacteristic timeCharacteristic) |
public static final int DEFAULT_LOWER_BOUND_MAX_PARALLELISM
public static final TimeCharacteristic DEFAULT_TIME_CHARACTERISTIC
public static final String DEFAULT_STREAMING_JOB_NAME
public static final String DEFAULT_BATCH_JOB_NAME
public static final String DEFAULT_SLOT_SHARING_GROUP
protected static Integer iterationIdCounter
public StreamGraphGenerator(List<Transformation<?>> transformations, ExecutionConfig executionConfig, CheckpointConfig checkpointConfig)
public StreamGraphGenerator(List<Transformation<?>> transformations, ExecutionConfig executionConfig, CheckpointConfig checkpointConfig, Configuration configuration)
public static int getNewIterationNodeId()
public StreamGraphGenerator setStateBackend(StateBackend stateBackend)
public StreamGraphGenerator setTimeCharacteristic(TimeCharacteristic timeCharacteristic)
public StreamGraphGenerator setSlotSharingGroupResource(Map<String,ResourceProfile> slotSharingGroupResources)
Note that a slot sharing group hints the scheduler that the grouped operators CAN be deployed into a shared slot. There's no guarantee that the scheduler always deploy the grouped operators together. In cases grouped operators are deployed into separate slots, the slot resources will be derived from the specified group requirements.
public void setSavepointRestoreSettings(SavepointRestoreSettings savepointRestoreSettings)
public StreamGraph generate()
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