Github user joewitt commented on a diff in the pull request:
https://github.com/apache/nifi/pull/1682#discussion_r112322877
--- Diff:
nifi-nar-bundles/nifi-standard-services/nifi-record-serialization-services-bundle/nifi-record-serialization-services/src/main/java/org/apache/nifi/grok/GrokReader.java
---
@@ -23,38 +23,58 @@
import java.io.Reader;
import java.util.ArrayList;
import java.util.List;
+import java.util.Map;
+import java.util.regex.Matcher;
import org.apache.nifi.annotation.documentation.CapabilityDescription;
import org.apache.nifi.annotation.documentation.Tags;
import org.apache.nifi.annotation.lifecycle.OnEnabled;
+import org.apache.nifi.components.AllowableValue;
import org.apache.nifi.components.PropertyDescriptor;
import org.apache.nifi.controller.ConfigurationContext;
import org.apache.nifi.flowfile.FlowFile;
import org.apache.nifi.logging.ComponentLog;
import org.apache.nifi.processor.util.StandardValidators;
+import org.apache.nifi.schema.access.SchemaAccessStrategy;
+import org.apache.nifi.schema.access.SchemaNotFoundException;
+import org.apache.nifi.schemaregistry.services.SchemaRegistry;
import org.apache.nifi.serialization.RecordReader;
-import org.apache.nifi.serialization.RowRecordReaderFactory;
-import org.apache.nifi.serialization.SchemaRegistryRecordReader;
+import org.apache.nifi.serialization.RecordReaderFactory;
+import org.apache.nifi.serialization.SchemaRegistryService;
+import org.apache.nifi.serialization.SimpleRecordSchema;
+import org.apache.nifi.serialization.record.DataType;
+import org.apache.nifi.serialization.record.RecordField;
+import org.apache.nifi.serialization.record.RecordFieldType;
import org.apache.nifi.serialization.record.RecordSchema;
import io.thekraken.grok.api.Grok;
+import io.thekraken.grok.api.GrokUtils;
import io.thekraken.grok.api.exception.GrokException;
@Tags({"grok", "logs", "logfiles", "parse", "unstructured", "text",
"record", "reader", "regex", "pattern", "logstash"})
@CapabilityDescription("Provides a mechanism for reading unstructured text
data, such as log files, and structuring the data "
+ "so that it can be processed. The service is configured using Grok
patterns. "
+ "The service reads from a stream of data and splits each message
that it finds into a separate Record, each containing the fields that are
configured. "
- + "If a line in the input does not match the expected message pattern,
the line of text is considered to be part of the previous "
- + "message, with the exception of stack traces. A stack trace that is
found at the end of a log message is considered to be part "
- + "of the previous message but is added to the 'STACK_TRACE' field of
the Record. If a record has no stack trace, it will have a NULL value "
- + "for the STACK_TRACE field. All fields that are parsed are
considered to be of type String by default. If there is need to change the type
of a field, "
- + "this can be accomplished by configuring the Schema Registry to use
and adding the appropriate schema.")
-public class GrokReader extends SchemaRegistryRecordReader implements
RowRecordReaderFactory {
+ + "If a line in the input does not match the expected message pattern,
the line of text is either considered to be part of the previous "
+ + "message or is skipped, depending on the configuration,, with the
exception of stack traces. A stack trace that is found at the end of "
+ + "a log message is considered to be part of the previous message but
is added to the 'stackTrace' field of the Record. If a record has "
+ + "no stack trace, it will have a NULL value for the stackTrace field.
All fields that are parsed are considered to be of type String by default. "
--- End diff --
Does the stack trace reference here make sense for general Grok
consumption? I mean, isn't that just a function of a given log file and
whether or not to capture it depends on a given grok expression? Or is this a
first class concept that we should be talking about here?
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