Config description changes for aggregate and anomaly detector processors.

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/AggregateProcessorConfig.java

@@ -6,6 +6,7 @@
 package org.opensearch.dataprepper.plugins.processor.aggregate;
 
 import org.opensearch.dataprepper.model.configuration.PluginModel;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import jakarta.validation.constraints.AssertTrue;
 import jakarta.validation.constraints.NotEmpty;
@@ -18,27 +19,36 @@ public class AggregateProcessorConfig {
 
     static int DEFAULT_GROUP_DURATION_SECONDS = 180;
 
+    @JsonPropertyDescription("An unordered list by which to group events. Events with the same values as these keys are put into the same group. If an event does not contain one of the identification_keys, then the value of that key is considered to be equal to null. At least one identification_key is required (for example, [\"sourceIp\", \"destinationIp\", \"port\"].")
     @JsonProperty("identification_keys")
     @NotEmpty
     private List<String> identificationKeys;
 
+    @JsonPropertyDescription("The amount of time that a group should exist before it is concluded automatically. Supports ISO_8601 notation strings (\"PT20.345S\", \"PT15M\", etc.) as well as simple notation for seconds (\"60s\") and milliseconds (\"1500ms\"). Default value is 180s.")
     @JsonProperty("group_duration")
     private Duration groupDuration = Duration.ofSeconds(DEFAULT_GROUP_DURATION_SECONDS);
 
+    @JsonPropertyDescription("The action to be performed on each group. One of the available aggregate actions must be provided, or you can create custom aggregate actions. remove_duplicates and put_all are the available actions. For more information, see Creating New Aggregate Actions.")
     @JsonProperty("action")
     @NotNull
     private PluginModel aggregateAction;
 
+    @JsonPropertyDescription("When local_mode is set to true, the aggregation is performed locally on each Data Prepper node instead of forwarding events to a specific node based on the identification_keys using a hash function. Default is false.")
     @JsonProperty("local_mode")
     @NotNull
     private Boolean localMode = false;
 
+    @JsonPropertyDescription("A boolean indicating if the unaggregated events should be forwarded to the next processor/sink in the chain.")
     @JsonProperty("output_unaggregated_events")
     private Boolean outputUnaggregatedEvents = false;
 
+    @JsonPropertyDescription("Tag to be used for aggregated events to distinguish aggregated events from unaggregated events.")
     @JsonProperty("aggregated_events_tag")
     private String aggregatedEventsTag;
 
+    @JsonPropertyDescription("A [conditional expression](https://opensearch.org/docs/latest/data-prepper/pipelines/expression-syntax/), " +
+            "such as `/some-key == \"test\"'`, that will be evaluated to determine whether the processor will be " +
+            "run on the event. Default is `null`. All events will be processed unless otherwise stated.")
     @JsonProperty("aggregate_when")
     private String whenCondition;
 

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/AppendAggregateActionConfig.java

@@ -8,9 +8,11 @@
 import java.util.List;
 
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 
 public class AppendAggregateActionConfig {
 
+    @JsonPropertyDescription("list of keys to append.")
     @JsonProperty("keys_to_append")
     List<String> keysToAppend;
 

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/CountAggregateActionConfig.java

@@ -9,6 +9,7 @@
 import java.util.List;
 import java.util.Set;
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 
 public class CountAggregateActionConfig {
     static final String SUM_METRIC_NAME = "count";
@@ -17,21 +18,27 @@ public class CountAggregateActionConfig {
     public static final String DEFAULT_END_TIME_KEY = "aggr._end_time";
     public static final Set<String> validOutputFormats = new HashSet<>(Set.of(OutputFormat.OTEL_METRICS.toString(), OutputFormat.RAW.toString()));
 
+    @JsonPropertyDescription("Key used for storing the count. Default name is aggr._count.")
     @JsonProperty("count_key")
     String countKey = DEFAULT_COUNT_KEY;
 
+    @JsonPropertyDescription("Metric name to be used when otel format is used.")
     @JsonProperty("metric_name")
     String metricName = SUM_METRIC_NAME;
 
+    @JsonPropertyDescription("List of unique keys to count.")
     @JsonProperty("unique_keys")
     List<String> uniqueKeys = null;
 
+    @JsonPropertyDescription("Key used for storing the start time. Default name is aggr._start_time.")
     @JsonProperty("start_time_key")
     String startTimeKey = DEFAULT_START_TIME_KEY;
 
+    @JsonPropertyDescription("Key used for storing the end time. Default name is aggr._end_time.")
     @JsonProperty("end_time_key")
     String endTimeKey = DEFAULT_END_TIME_KEY;
 
+    @JsonPropertyDescription("Format of the aggregated event.otel_metrics: Default output format. Outputs in OTel metrics SUM type with count as value.raw - Generates a JSON object with the count_key field as a count value and the start_time_key field with aggregation start time as value.")
     @JsonProperty("output_format")
     String outputFormat = OutputFormat.OTEL_METRICS.toString();
 

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/HistogramAggregateActionConfig.java

@@ -9,6 +9,7 @@
 import java.util.List;
 import java.util.HashSet;
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.validation.constraints.NotNull;
 
 public class HistogramAggregateActionConfig {
@@ -25,27 +26,34 @@ public class HistogramAggregateActionConfig {
     public static final String DURATION_KEY = "duration";
     public static final Set<String> validOutputFormats = new HashSet<>(Set.of(OutputFormat.OTEL_METRICS.toString(), OutputFormat.RAW.toString()));
 
+    @JsonPropertyDescription("Name of the field in the events the histogram generates.")
     @JsonProperty("key")
     @NotNull
     String key;
 
+    @JsonPropertyDescription("The units for the values in the key.")
     @JsonProperty("units")
     @NotNull
     String units;
 
+    @JsonPropertyDescription("Metric name to be used when otel format is used.")
     @JsonProperty("metric_name")
     String metricName = HISTOGRAM_METRIC_NAME;
 
+    @JsonPropertyDescription("key_prefix used by all the fields created in the aggregated event. Having a prefix ensures that the names of the histogram event do not conflict with the field names in the event.")
     @JsonProperty("generated_key_prefix")
     String generatedKeyPrefix = DEFAULT_GENERATED_KEY_PREFIX;
 
+    @JsonPropertyDescription("A list of buckets (values of type double) indicating the buckets in the histogram.")
     @JsonProperty("buckets")
     @NotNull
     List<Number> buckets;
 
+    @JsonPropertyDescription("Format of the aggregated event.otel_metrics: Default output format. Outputs in OTel metrics SUM type with count as value.raw - Generates a JSON object with the count_key field as a count value and the start_time_key field with aggregation start time as value.")
     @JsonProperty("output_format")
     String outputFormat = OutputFormat.OTEL_METRICS.toString();
 
+    @JsonPropertyDescription("A Boolean value indicating whether the histogram should include the min and max of the values in the aggregation.")
     @JsonProperty("record_minmax")
     boolean recordMinMax = false;
 

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/PercentSamplerAggregateActionConfig.java

@@ -7,9 +7,11 @@
 
 import com.fasterxml.jackson.annotation.JsonProperty;
 import jakarta.validation.constraints.NotNull;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.validation.constraints.AssertTrue;
 
 public class PercentSamplerAggregateActionConfig {
+    @JsonPropertyDescription("Percent value of the sampling to be done.")
     @JsonProperty("percent")
     @NotNull
     private double percent;

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/RateLimiterAggregateActionConfig.java

@@ -8,15 +8,18 @@
 import java.util.Set;
 import java.util.HashSet;
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.validation.constraints.NotNull;
 
 public class RateLimiterAggregateActionConfig {
     public static final Set<String> validRateLimiterModes = new HashSet<>(Set.of(RateLimiterMode.BLOCK.toString(), RateLimiterMode.DROP.toString()));
 
+    @JsonPropertyDescription("The number of events allowed per second.")
     @JsonProperty("events_per_second")
     @NotNull
     int eventsPerSecond;
 
+    @JsonPropertyDescription("Indicates what action the rate_limiter takes when the number of events received is greater than the number of events allowed per second. Default value is block, which blocks the processor from running after the maximum number of events allowed per second is reached until the next second. Alternatively, the drop option drops the excess events received in that second.")
     @JsonProperty("when_exceeds")
     String whenExceedsMode = RateLimiterMode.BLOCK.toString();
 

data-prepper-plugins/aggregate-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/aggregate/actions/TailSamplerAggregateActionConfig.java

@@ -6,20 +6,24 @@
 package org.opensearch.dataprepper.plugins.processor.aggregate.actions;
 
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.validation.constraints.NotNull;
 import jakarta.validation.constraints.AssertTrue;
 
 import java.time.Duration;
 
 public class TailSamplerAggregateActionConfig {
+    @JsonPropertyDescription("period to wait before considering that a trace event is complete")
     @JsonProperty("wait_period")
     @NotNull
     private Duration waitPeriod;
 
+    @JsonPropertyDescription("percent value to use for sampling non error events.")
     @JsonProperty("percent")
     @NotNull
     private Integer percent;
 
+    @JsonPropertyDescription("condition that determines if an event is error event or not")
     @JsonProperty("condition")
     private String condition;
 

data-prepper-plugins/anomaly-detector-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/anomalydetector/AnomalyDetectorProcessorConfig.java

@@ -6,6 +6,7 @@
 package org.opensearch.dataprepper.plugins.processor.anomalydetector;
 
 import org.opensearch.dataprepper.model.configuration.PluginModel;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import com.fasterxml.jackson.annotation.JsonProperty;
 import jakarta.validation.constraints.NotEmpty;
 import jakarta.validation.constraints.NotNull;
@@ -14,20 +15,25 @@
 import java.util.List;
 
 public class AnomalyDetectorProcessorConfig {
+    @JsonPropertyDescription("The ML algorithm (or model) used to detect anomalies. You must provide a mode. See random_cut_forest mode.")
     @JsonProperty("mode")
     @NotNull
     private PluginModel detectorMode;
 
+    @JsonPropertyDescription("A non-ordered List<String> that is used as input to the ML algorithm to detect anomalies in the values of the keys in the list. At least one key is required.")
     @JsonProperty("keys")
     @NotEmpty
     private List<String> keys;
 
+    @JsonPropertyDescription("If provided, anomalies will be detected within each unique instance of these keys. For example, if you provide the ip field, anomalies will be detected separately for each unique IP address.")
     @JsonProperty("identification_keys")
     private List<String> identificationKeys = Collections.emptyList();
 
+    @JsonPropertyDescription("RCF will try to automatically learn and reduce the number of anomalies detected. For example, if latency is consistently between 50 and 100, and then suddenly jumps to around 1000, only the first one or two data points after the transition will be detected (unless there are other spikes/anomalies). Similarly, for repeated spikes to the same level, RCF will likely eliminate many of the spikes after a few initial ones. This is because the default setting is to minimize the number of alerts detected. Setting the verbose setting to true will cause RCF to consistently detect these repeated cases, which may be useful for detecting anomalous behavior that lasts an extended period of time.")
     @JsonProperty("verbose")
     private Boolean verbose = false;
 
+    @JsonPropertyDescription("If using the identification_keys settings, a new ML model will be created for every degree of cardinality. This can cause a large amount of memory usage, so it is helpful to set a limit on the number of models. Default limit is 5000.")
     @JsonProperty("cardinality_limit")
     private int cardinalityLimit = 5000;
 

data-prepper-plugins/anomaly-detector-processor/src/main/java/org/opensearch/dataprepper/plugins/processor/anomalydetector/modes/RandomCutForestModeConfig.java

@@ -6,6 +6,7 @@
 package org.opensearch.dataprepper.plugins.processor.anomalydetector.modes;
 
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonPropertyDescription;
 import jakarta.validation.constraints.AssertTrue;
 
 import java.util.Set;
@@ -25,22 +26,27 @@ public class RandomCutForestModeConfig {
 
     public static final String VERSION_1_0 = "1.0";
 
+    @JsonPropertyDescription("The algorithm version number.")
     @JsonProperty("version")
     private String version = VERSION_1_0;
 
     public static final Set<String> validVersions = new HashSet<>(Set.of(VERSION_1_0));
 
+    @JsonPropertyDescription("The type of data sent to the algorithm.")
     @JsonProperty("type")
     private String type = RandomCutForestType.METRICS.toString();
 
     public static final Set<String> validTypes = new HashSet<>(Set.of(RandomCutForestType.METRICS.toString()));
 
+    @JsonPropertyDescription("The shingle size used in the ML algorithm.")
     @JsonProperty("shingle_size")
     private int shingleSize = DEFAULT_SHINGLE_SIZE;
 
+    @JsonPropertyDescription("The sample size used in the ML algorithm.")
     @JsonProperty("sample_size")
     private int sampleSize = DEFAULT_SAMPLE_SIZE;
 
+    @JsonPropertyDescription("The time decay value used in the ML algorithm. Used as the mathematical expression timeDecay divided by SampleSize in the ML algorithm.")
     @JsonProperty("time_decay")
     private double timeDecay = DEFAULT_TIME_DECAY;