Requirements
Generic Token support (not only MR counters)
- Ability for the user to access the token set by any node in the Workflow
- Persist token per Workflow run in the MDS
- View token set by specific node in the Workflow
Assumptions
Generic information in the token is of the key-value type, each represented by String.
Potential Changes
WorkflowToken interface changes
...
User Stories
As a developer of the Workflow application -
- I want the ability to pass the custom data (such as metric, status, error codes etc.) from one program in the Workflow to the next subsequent programs in the form of a token.
- At any node in the Workflow, I want ability to query the data from the token.
- I want ability to fetch the data from the token which was set by a specific node.
- I want ability to find the name of the node which most recently set the token value for a specific key; e.g., the node who last set the ERROR flag in the token, so that I can take appropriate action (such as logging or improving its code) on it.
- I want to have the conditional execution in the Workflow based on the information contained in the token.
- I want to terminate the execution if a node in the Workflow produces unexpected results.
As an admin/support person/developer of the Workflow application -
- I want the ability to query the WorkflowToken from the past runs for running analysis such as which node is executed more frequently and why.
- I want the ability to query the token values which were added by a specific node in the Workflow to debug the flow of execution.
Requirements
Generic Token support (not only MR counters)
- Ability for the user to access the token set by any node in the Workflow
- Persist token per Workflow run in the MDS
- View token set by specific node in the Workflow
Assumptions
Generic information in the token is of the key-value type, each represented by String.
Potential Changes
WorkflowToken interface changes
Code Block /** * Interface to represent the data that is transferred from one node to the next nodes in the {@link Workflow}. */ @Beta public interface WorkflowToken { /** * Keys in the {@link WorkflowToken} can be added by user, using the * {@link WorkflowToken#put} method. These keys are added under the {@link Scope#USER} scope. * CDAP also adds some keys to the {@link WorkflowToken}. for e.g. MapReduce counters. * The keys added by CDAP gets added under {@link Scope#SYSTEM} scope. */ public enum Scope { USER, SYSTEM } /** * Put the specified key and value into the {@link WorkflowToken}. * The token may store additional information about the context in which * this key is being set, for example, the unique name of the workflow node. * @param key the key representing the entry * @param value the value for the key */ void put(String key, String value); /** * Put the specified key and {@link Value} into the {@link WorkflowToken}. * The token may store additional information about the context in which * this key is being set, for example, the unique name of the workflow node. * @param key the key torepresenting entry be searched * @param nodeNamevalue the name{@link of the node * @return the value set Value} for the key by nodeName */ @Nullable Stringvoid getValueput(String key, StringValue nodeNamevalue); /** * Get the most recent value added for the specified key for a {@link Scope#USER} scope. * @param key the key to be searched * @return the value{@link Value} for the key or *<code>null</code> if @Nullablethe Stringkey getValue(String key);does not /** * Returnexist truein if the {@link WorkflowTokenScope#USER} contains thescope specified key. */ @param key the@Nullable key to beValue tested for the presence in the {@link WorkflowToken}get(String key); /** * @returnGet the result ofmost recent value for the testspecified key */for booleana containsKey(String key); /**given scope. * This@param methodkey isthe deprecatedkey asto ofbe releasesearched 3.1. User can override* @param scope * the {@link MapReduce#onFinishWorkflowToken.Scope} method and putfor the hadoop counterskey in the * WorkflowToken@return ifthe required.{@link Value} *for the *key Getfrom the Hadoopspecified countersscope fromor the<code>null</code> previousif MapReducethe program inkey the Workflow. * Thedoes methodnot returnsexist nullin if the countersgiven arescope not set. */ @return the Hadoop@Nullable MapReduce counters set by the previous MapReduce program */ @Deprecated @Nullable Map<String, Map<String, Long>> getMapReduceCounters();
WorkflowConfigurer interface changes
We generate unique numeric node ids for each node when the application is deployed. However, while writing the Workflow, users will not be aware of the node id associated with each node in the Workflow. Since WorkflowToken stores the MapReduce counters and other information per node level, users should be able to get the value of a particular key from the token as set by the particular program in the Workflow.
If the program is used only once in a Workflow, then the user can use its name to query for the token information. However, we allow the same program to occur multiple times in a Workflow. In that case, the program name will not be sufficient to access the token.
The WorkflowConfigurer API can be updated to allow a user to set a unique name for the program, if it occurs multiple times in a Workflow and use that unique name to retrieve the token.
WorkflowToken can also be updated from a predicate on the condition node. In the presence of multiple condition nodes in a Workflow, we will need the ability to specify unique names for the conditions as well so that token values from specific condition nodes can be fetched.Code Block /** * Add MapReduce program to the {@link Workflow}. * @param uniqueName the unique name for the MapReduce program which will be used * to identify particular occurrence of the program in the Workflow * @param mapReduceName the name of the MapReduce program */ void addMapReduce(String uniqueName, String mapReduceName);
Provide ability to set and get information in the WorkflowTokenCode Block /** * Adds a condition with the unique name to the {@link Workflow}. * @param conditionName the unique name to be assigned to the condition * @param condition the {@link Predicate} to be evaluated for the condition * @return the configurer for the condition */ WorkflowConditionConfigurer<? extends WorkflowConfigurer> condition(String conditionName, Predicate<WorkflowContext> condition);
1. MapReduce program: Users should be able to access and modify WorkflowToken from "beforeSubmit" and "onFinish" methods of the MapReduce program. Since these methods get the MapReduceContext, we will need to update the MapReduceContext interface to get the WorkflowToken.Code Block /** * If {@link MapReduce} program is executed as a part of the {@link Workflow} * then get the {@link WorkflowToken} associated with the current run, otherwise return null. * @return the {@link WorkflowToken} if available */ @Nullable WorkflowToken getWorkflowToken();
Consider the following code sample to update the WorkflowToken in the MapReduce program:
Code Block @Override public void beforeSubmit(MapReduceContext context) throws Exception { ... WorkflowToken workflowToken = context.getWorkflowToken(); if (workflowToken != null) { // Put the action type in the WorkflowToken workflowToken.setValue("action", "MAPREDUCE"); // Put the start time for the action workflowToken.setValue("startTime", String.valueOf(System.currentTimeMillis())); } ... } @Override public void onFinish(boolean succeeded, MapReduceContext context) throws Exception { ... // if job is successful put hadoop counters in the WorkflowToken WorkflowToken workflowToken = context.getWorkflowToken(); if (workflowToken != null) { // Put the end time for the action workflowToken.setValue("endTime", String.valueOf(System.currentTimeMillis())); // Put counters in the WorkflowToken workflowToken.setValue("counters", getHadoopCounters(context.getHadoopJob())); } ... } // Method returns the hadoop counters in JSON format private static String getHadoopCounters(Job job) throws Exception { Map<String, Map<String, Long>> mapReduceCounters = Maps.newHashMap(); Counters counters = job.getCounters(); for (CounterGroup group : counters) { mapReduceCounters.put(group.getName(), new HashMap<String, Long>()); for (Counter counter : group) { mapReduceCounters.get(group.getName()).put(counter.getName(), counter.getValue()); } } return new Gson().toJson(mapReduceCounters); }
2. Spark program: Users should be able to access and modify WorkflowToken from "beforeSubmit" and "onFinish" methods of the Spark program. Since these methods get the SparkContext, we will need to update the SparkContext interface to get the WorkflowToken.
3. Custom Workflow action: Since custom workflow actions already receive WorkflowContext, no changes are anticipated in the interface.Code Block /** * If {@link Spark} program is executed as a part of the {@link Workflow} * then get the {@link WorkflowToken} associated with the current run, otherwise return null. * @return the {@link WorkflowToken} if available */ @Nullable WorkflowToken getWorkflowToken();
Following is the sample code to get values from the WorkflowToken in custom action:
WorkflowToken in presence of Fork and JoinCode Block @Override public void run() { ... WorkflowToken token = getContext().getToken(); // set the type of the action of the current node token.setValue("action", "CUSTOM_ACTION"); // Assuming that every node in the Workflow adds the key "action" with the value as action type in the WorkflowToken Map<String, String> nodeValues = token.getValues("action"); // To get the number of nodes executed by the Workflow - nodeValues.size(); // Simply iterate over the nodeValues.keySet() to get the order in which the nodes were executed. // To get the start time of the MapReduce program with unique name "PurchaseHistoryBuilder" String startTime = token.getValues("startTime").get("PurchaseHistoryBuilder"); // To get the MapReduce counters set by MapReduce program with unique name "PurchaseHistoryBuilder" Type mapReduceCounterType = new TypeToken<Map<String, Map<String, Long>>>() {}.getType(); Map<String, Map<String, Long>> counters = new Gson().fromJson(token.getValues("counters").get("PurchaseHistoryBuilder"), mapReduceCounterType); ... }
When a fork is encountered in the Workflow, we make a copy of the WorkflowToken and pass it along to each branch. At the join, we create a new WorkflowToken, which will be a merge of the WorkflowTokens associated with each of the branches of the fork. Since we are storing the information in the token at the node level, there will not be any conflicts during the merge process.
Persisting the WorkflowToken
The RunRecord for the Workflow will contain the WorkflowToken as its property. This token will be updated before the execution of the action in the Workflow. We will add a version field to the RunRecord itself which will help in the upgrade process.RESTful end-points to access the value of the WorkflowToken that was received by an individual node in the WorkflowWe will expose a RESTful end point to retrieve the token values that were set by a particular node as identified by its unique name. /Code Block Value get(String key, Scope scope); /** * Get the value set for the specified key by the specified node for a {@link Scope#USER} scope. * @param key the key to be searched * @param nodeName the name of the node * @return the {@link Value} set for the key by nodeName or <code>null</code> if the key is not * added by the nodeName in the {@link Scope#USER} scope */ @Nullable Value get(String key, String nodeName); /** * Get the value set for the specified key by the specified node for a given scope. * @param key the key to be searched * @param nodeName the name of the node * @param scope the {@link WorkflowToken.Scope} for the key * @return the {@link Value} set for the key by nodeName for a given scope or <code>null</code> * if the key is not added by the nodeName in the given scope */ @Nullable Value get(String key, String nodeName, Scope scope); /** * Same key can be added to the {@link WorkflowToken} by multiple nodes. * This method returns the {@link List} of {@link NodeValue}, where * each entry represents the unique node name and the {@link Value} that it set * for the specified key for a {@link Scope#USER} scope. * <p> * The list maintains the order in which the values were * inserted in the WorkflowToken for a specific key except in the case of fork * and join. In case of fork in the Workflow, copies of the WorkflowToken are made * and passed along each branch. At the join, all copies of the * WorkflowToken are merged together. While merging, the order in which the values were * inserted for a specific key is guaranteed within the same branch, but not across * different branches. * @param key the key to be searched * @return the list of {@link NodeValue} from node name to the value that node * added for the input key */ List<NodeValue> getAll(String key); /** * Same key can be added to the WorkflowToken by multiple nodes. * This method returns the {@link List} of {@link NodeValue}, where * each entry represents the unique node name and the {@link Value} that it set * for the specified key for a given scope. * <p> * The list maintains the order in which the values were * inserted in the WorkflowToken for a specific key except in the case of fork * and join. In case of fork in the Workflow, copies of the WorkflowToken are made * and passed along each branch. At the join, all copies of the * WorkflowToken are merged together. While merging, the order in which the values were * inserted for a specific key is guaranteed within the same branch, but not across * different branches. * @param key the key to be searched * @param scope the {@link WorkflowToken.Scope} for the key * @return the list of {@link NodeValue} from node name to the value that node * added for the input key for a given scope */ List<NodeValue> getAll(String key, Scope scope); /** * Get the {@link Map} of key to {@link Value}s that were added to the {@link WorkflowToken} * by specific node for a {@link Scope#USER} scope. * @param nodeName the unique name of the node * @return the map of key to values that were added by the specified node */ Map<String, Value> getAllFromNode(String nodeName); /** * Get the {@link Map} of key to {@link Value}s that were added to the {@link WorkflowToken} * by specific node for a given scope. * @param nodeName the unique name of the node * @param scope the {@link WorkflowToken.Scope} for the key * @return the map of key to values that were added by the specified node for a given scope */ Map<String, Value> getAllFromNode(String nodeName, Scope scope); /** * Same key can be added to the WorkflowToken by multiple nodes. * This method returns the key to {@link List} of {@link NodeValue} * added in the {@link Scope#USER} scope. * @return the {@link Map} of key to {@link List} of {@link NodeValue} added for * the given scope */ Map<String, List<NodeValue>> getAll(); /** * Same key can be added to the WorkflowToken by multiple nodes. * This method returns the key to {@link List} of {@link NodeValue} * added in the {@link WorkflowToken.Scope} provided. * @param scope the scope for the key * @return the {@link Map} of key to {@link List} of {@link NodeValue} added for * the given scope */ Map<String, List<NodeValue>> getAll(Scope scope); /** * This method is deprecated as of release 3.1. * Get the Hadoop counters from the previous MapReduce program in the Workflow. * The method returns null if the counters are not set. * @return the Hadoop MapReduce counters set by the previous MapReduce program */ @Deprecated @Nullable Map<String, Map<String, Long>> getMapReduceCounters(); }
The method getAll(String key) in the above interface returns the List of NodeValue objects. NodeValue class represents nodeName and value that the node put for the specific key.Code Block /** * Multiple nodes in the Workflow can add the same key to the {@link WorkflowToken}. * This class provides a mapping from node name to the {@link Value} which was set for the * specific key. */ public final class NodeValue implements Serializable { private static final long serialVersionUID = 6157808964174399650L; private final String nodeName; private final Value value; public NodeValue(String nodeName, Value value) { this.nodeName = nodeName; this.value = value; } public String getNodeName() { return nodeName; } public Value getValue() { return value; } ... // other methods like toString(), equals() and hashCode() ... }
The details of the Value class are as follows:
Code Block /** * Class representing the value of the key in the {@link WorkflowToken}. */ public class Value implements Serializable { private static final long serialVersionUID = -3420759818008526875L; private final String value; private Value(String value) { this.value = value; } /** * @return the boolean value */ public boolean getAsBoolean() { return Boolean.parseBoolean(value); } /** * @return the int value */ public int getAsInt() { return Integer.parseInt(value); } /** * @return the long value */ public long getAsLong() { return Long.parseLong(value); } /** * @return the String value */ @Override public String toString() { return value; } }
Ability to include same program multiple times in the Workflow
This can be achieved without making any changes to the API. Consider the following use case -
Use Case: Email campaign generates two categories of events - send events (SUCCESS, FAIL) and tracking events (OPEN, CLICK etc.). Records representing the send event and tracking event have different schema. These two categories of the events are sent to CDAP using streams "send" and "tracking".
Tracking event format:
audience_id,event_type,ip_address,device_type,event_time,link
Example records:
bob,CLICK,192.168.29.10,android,1436311150092,http://www.somedomain.com
adam,CLICK,192.168.29.18,ipad,1436311232276,http://www.anotherdomain.com
Send event format:
audience_id::event_sub_type::ip_address::deliveryCode::event_time
Example records:
bob::SEND::192.168.29.10::SUCCESS::1436311232276
adam::SEND::192.168.29.9::SUCCESS::1436311434476
Same MapReduce program "EventParser" can be used in the Workflow to parse these two categories of the events in parallel and create the list Event object per audience id.
EventParser application:
Code Block language java public class EventParserApp extends AbstractApplication { @Override public void configure() { // Stream to receive send events addStream(new Stream("send")); // Stream to receive tracking events addStream(new Stream("tracking")); // Add EventParser MapReduce program multiple times in the application with different properties Map<String, String> properties = Maps.newHashMap(); properties.put("input.stream", "tracking"); // 'trackingParser' is instance of the EventParser which will read the 'tracking' stream addMapReduce(new EventParser("trackingParser", properties)); properties = Maps.newHashMap(); properties.put("input.stream", "send"); // 'sendParser' is instance of the EventParser which will read the 'send' stream addMapReduce(new EventParser("sendParser", properties)); // Add Workflow which will process the tracking and send events in parallel addWorkflow(new EventParserWorkflow()); } }
EventParser MapReduce program:
Code Block language java public class EventParser extends AbstractMapReduce { private final String name; private final Map<String, String> properties; public EventParser(String name, Map<String, String> properties) { this.name = name; this.properties = properties; } @Override public void configure() { setName(name); setDescription("MapReduce program for parsing the email events and storing them in the dataset."); // Serialize the properties setProperties(properties); setOutputDataset("events"); } @Override public void beforeSubmit(MapReduceContext context) throws Exception { Job job = context.getHadoopJob(); job.setMapperClass(EventParserMapper.class); job.setReducerClass(EventParserReducer.class); job.setMapOutputKeyClass(Text.class); job.setOutputValueClass(Event.class); job.setNumReduceTasks(1); String streamToVerify = context.getSpecification().getProperties().get("input.stream"); job.getConfiguration().set("input.stream", streamToVerify); // Read the purchase events from the last 60 minutes as input to the mapper. final long endTime = context.getLogicalStartTime(); final long startTime = endTime - TimeUnit.MINUTES.toMillis(60); StreamBatchReadable.useStreamInput(context, streamToVerify, startTime, endTime); } } // EventParserMapper public static class EventParserMapper extends Mapper<LongWritable, Text, Text, Event> { @Override public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String logEvent = value.toString(); if (logEvent.isEmpty()) { return; } String inputStream = context.getConfiguration().get("input.stream"); Event event; if(inputStream.equals("send")) { event = getSendEvent(logEvent); } else { event = getTrackingEvent(logEvent); } if (event != null) { context.write(new Text(event.getAudienceId()), event); } } private Event getSendEvent(String logEvent) { String seperator = "::"; int fieldLength = 5; String[] fields = logEvent.split(seperator); if (fields.length != fieldLength) { return null; } String audienceId = fields[0]; String eventType = fields[1]; String ipAddress = fields[2]; String deliveryCode = fields[3]; String eventTime = fields[4]; return new Event(audienceId, eventType, ipAddress, eventTime, deliveryCode) } private Event getTrackingEvent(String logEvent) { String seperator = ","; int fieldLength = 6; String[] fields = logEvent.split(seperator); if (fields.length != fieldLength) { return null; } String audienceId = fields[0]; String eventType = fields[1]; String ipAddress = fields[2]; String deviceType = fields[3]; String eventTime = fields[4]; String link = fields[5]; return new Event(audienceId, eventType, ipAddress, eventTime, deviceType + "&&" + link); } }
EventParserWorkflow:
Code Block language java public class EventParserWorkflow extends AbstractWorkflow { @Override protected void configure() { fork() .addMapReduce("trackingParser") .also() .addMapReduce("sendParser") .join(); } }
Provide ability to set and get information in the WorkflowToken
1. MapReduce program: Users should be able to access and modify WorkflowToken from "beforeSubmit" and "onFinish" methods of the MapReduce program. Since these methods get the MapReduceContext, we will need to update the MapReduceContext interface to get the WorkflowToken.Code Block /** * If {@link MapReduce} program is executed as a part of the {@link Workflow} * then get the {@link WorkflowToken} associated with the current run, otherwise return null. * @return the {@link WorkflowToken} if available */ @Nullable WorkflowToken getWorkflowToken();
Consider the following code sample to update the WorkflowToken in the MapReduce program:
Code Block @Override public void beforeSubmit(MapReduceContext context) throws Exception { ... WorkflowToken workflowToken = context.getWorkflowToken(); if (workflowToken != null) { // Put the action type in the WorkflowToken workflowToken.put("action.type", "MAPREDUCE"); // Put the start time for the action workflowToken.put("start.time", String.valueOf(System.currentTimeMillis())); } ... } @Override public void onFinish(boolean succeeded, MapReduceContext context) throws Exception { ... WorkflowToken workflowToken = context.getWorkflowToken(); if (workflowToken != null) { // Put the end time for the action workflowToken.put("end.time", String.valueOf(System.currentTimeMillis())); } ... }
2. Spark program: Users should be able to access and modify WorkflowToken from "beforeSubmit" and "onFinish" methods of the Spark program. Since these methods get the SparkContext, we will need to update the SparkContext interface to get the WorkflowToken.
Code Block /** * If {@link Spark} program is executed as a part of the {@link Workflow} * then get the {@link WorkflowToken} associated with the current run, otherwise return null. * @return the {@link WorkflowToken} if available */ @Nullable WorkflowToken getWorkflowToken();
3. Custom Workflow action: Since custom workflow actions already receive WorkflowContext, no changes are anticipated in the interface.
Following is the sample code to get values from the WorkflowToken in custom action:
Code Block @Override public void run() { ... WorkflowToken token = getContext().getToken(); // set the type of the action of the current node token.put("action.type", "CUSTOM_ACTION"); // Assume that we have the following Workflow // |------->PurchaseByCustomer------->| // True | | // Start---->RecordVerifier---->Predicate-------->| |------------->StatusReporter----->End // | | | | // | False |------->PurchaseByProduct-------->| | // | | // |--------------------->ProblemLogger--------------------->| // Use case 1: Predicate can add the key "branch" in the WorkflowToken with value as "true" if true branch will be executed // or "false" otherwise. In "StatusReporter" in order to get which branch in the Workflow was executed boolean bTrueBranch = Boolean.parseBoolean(token.get("branch")); // Use case 2: User may want to compare the records emitted by "PurchaseByCustomer" and "PurchaseByProduct", in order to find which job // is generating more records. String flattenReduceOutputRecordsCounterName = "org.apache.hadoop.mapreduce.TaskCounter.REDUCE_OUTPUT_RECORDS"; String purchaseByCustomerCounterValue = token.get(flattenReduceOutputRecordsCounterName, "PurchaseByCustomer", WorkflowToken.Scope.SYSTEM); String purchaseByProductCounterValue = token.get(flattenReduceOutputRecordsCounterName, "PurchaseByProduct", WorkflowToken.Scope.SYSTEM); // Use case 3: Since Workflow can have multiple complex conditions and forks in its structure, in the "StatusReporter", // user may want to know how many actions were executed as a part of this run. If the number of nodes executed were below // certain threshold send an alert. Assuming that every node in the Workflow adds the key "action.type" with the value as action // type for node in the WorkflowToken, user can further figure out the break down by action type in the particular Workflow run. List<NodeValueEntry> nodeValues = token.getAll("action.type"); int totalNodeExecuted = nodeValues.size(); int mapReduceNodes = 0; int sparkNodes = 0; int customActionNodes = 0; int conditions = 0; for (NodeValueEntry entry : nodeValues) { if (entry.getValue().equals("MAPREDUCE")) { mapReduceNodes++; } if (entry.getValue().equals("SPARK")) { sparkNodes++; } if (entry.getValue().equals("CUSTOM_ACTION")) { customActionNodes++; } if (entry.getValue().equals("CONDITION")) { conditions++; } } // Use case 4: To get the name of the last node which set the "ERROR" flag in the WorkflowToken List<NodeValueEntry> errorNodeValueList = token.getAll("ERROR"); String nodeNameWhoSetTheErrorFlagLast = errorNodeValueList.get(errorNodeValueList.size() - 1); // To get the start time of the MapReduce program with unique name "PurchaseHistoryBuilder" String startTime = token.get("start.time", "PurchaseHistoryBuilder"); // To get the most recent value of counter with group name // 'org.apache.hadoop.mapreduce.TaskCounter' and counter name 'MAP_INPUT_RECORDS' String flattenCounterKey = "mr.counters.org.apache.hadoop.mapreduce.TaskCounter.MAP_INPUT_RECORDS"; workflowToken.get(flattenCounterKey, WorkflowToken.Scope.SYSTEM); // To get the value of counter with group name 'org.apache.hadoop.mapreduce.TaskCounter' // and counter name 'MAP_INPUT_RECORDS' as set by MapReduce program with unique name 'PurchaseHistoryBuilder' workflowToken.get(flattenCounterKey, "PurchaseHistoryBuilder", WorkflowToken.Scope.SYSTEM); ... }
- WorkflowToken in presence of Fork and Join
When a fork is encountered in the Workflow, we make a copy of the WorkflowToken and pass it along to each branch. At the join, we create a new WorkflowToken, which will be a merge of the WorkflowTokens associated with each of the branches of the fork. Since we are storing the information in the token at the node level, there will not be any conflicts during the merge process. - Persisting the WorkflowToken
The RunRecord for the Workflow will contain the WorkflowToken as its property. This token will be updated before the execution of the action in the Workflow. We will add a version field to the RunRecord itself which will help in the upgrade process. - RESTful end-points to access the value of the WorkflowToken that was received by an individual node in the Workflow1. To get the values that user put in the WorkflowToken for a particular run
Code Block language java /apps/{app-id}/workflows/{workflow-id}/runs/{run-id}/token
2. To get the values that CDAP put (e.g. MapReduce counters for MapReduce nodes) in the WorkflowToken for a particular run
Code Block /apps/{app-id}/workflows/{workflow-id}/runs/{run-id}/token?scope=system
3. To get the key values in the USER scope that particular node added to the WorkflowToken
Code Block /apps/{app-id}/workflows/{workflow-id}/runs/{run-id}/nodes/{node-id}/token
4. To get the key values in the SYSTEM scope that particular node added to the WorkflowToken
Code Block /apps/{app-id}/workflows/{workflow-id}/runs/{run-id}/nodes/{node-id}/token?scope=system
REST API Response Comments Reviewed? /namespaces/{namespace-id}/apps/{app-id}/workflows/{workflow-name}/runs/{run-id}/token Json containing the entire workflow token for a particular workflow run e.g.
Code Block { "tokenValueMap": { "key1": [ { "nodeName": "node1", "value": "value1" }, { "nodeName": "node2", "value": "value2" } ], "key2": [ { "nodeName": "node2", "value": "v2" } ] } }
Response Codes:
200 if successful
404 if app/workflow not found
500 if there is an internal error/namespaces/{namespace-id}/apps/{app-id}/workflows/{workflow-name}/runs/{run-id}/nodes/{unique-node-name}/token Code Block { "key1": "value1", "key2": "value2 }
Response Codes:
200 if successful
404 if app/workflow not found
500 if there is an internal error