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https://issues.apache.org/jira/browse/NIFI-1583?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15390910#comment-15390910
]
ASF GitHub Bot commented on NIFI-1583:
--------------------------------------
Github user mattyb149 commented on a diff in the pull request:
https://github.com/apache/nifi/pull/254#discussion_r71980960
--- Diff:
nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/ConvertJSONtoCSV.java
---
@@ -0,0 +1,360 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.nifi.processors.standard;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.commons.lang3.StringUtils;
+import org.apache.nifi.annotation.behavior.InputRequirement;
+import org.apache.nifi.annotation.behavior.WritesAttribute;
+import org.apache.nifi.annotation.documentation.CapabilityDescription;
+import org.apache.nifi.annotation.documentation.Tags;
+import org.apache.nifi.annotation.lifecycle.OnScheduled;
+import org.apache.nifi.components.AllowableValue;
+import org.apache.nifi.components.PropertyDescriptor;
+import org.apache.nifi.flowfile.FlowFile;
+import org.apache.nifi.processor.AbstractProcessor;
+import org.apache.nifi.processor.ProcessContext;
+import org.apache.nifi.processor.ProcessSession;
+import org.apache.nifi.processor.ProcessorInitializationContext;
+import org.apache.nifi.processor.Relationship;
+import org.apache.nifi.processor.exception.ProcessException;
+import org.apache.nifi.processor.io.StreamCallback;
+import org.apache.nifi.processor.util.StandardValidators;
+import org.json.JSONArray;
+import org.json.JSONException;
+import org.json.JSONObject;
+import org.json.JSONTokener;
+
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.OutputStream;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashSet;
+import java.util.Iterator;
+import java.util.LinkedHashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import java.util.SortedSet;
+import java.util.TreeSet;
+
+@Tags({"JSON, CSV, convert"})
+@InputRequirement(InputRequirement.Requirement.INPUT_REQUIRED)
+@WritesAttribute(attribute="mime.type", description="Sets the mime type to
application/csv")
+@CapabilityDescription("Converts a JSON document to CSV. This processor
reads the entire content " +
+ "of incoming FlowFiles into memory in order to perform the
conversion. The processor will parse JSON Arrays, JSON Objects " +
+ "and the combination of the two regardless of the level of nesting
in the JSON document.")
+public class ConvertJSONtoCSV extends AbstractProcessor {
+ volatile String delimiter;
+ volatile String removeFields;
+ volatile String emptyFields = "";
+
+ public static final AllowableValue INCLUDE_HEADER_TRUE = new
AllowableValue(
+ "True", "True", "Creates headers for each JSON file.");
+ public static final AllowableValue INCLUDE_HEADER_FALSE = new
AllowableValue(
+ "False", "False", "Only parses the JSON fields and does not
include headers");
+
+
+ public static final PropertyDescriptor DELIMITER = new
PropertyDescriptor
+ .Builder().name("CSV Delimiter")
+ .description("Delimiter used for the generated CSV output
(Example: , | -)")
+ .required(true)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor REMOVE_FIELDS = new
PropertyDescriptor
+ .Builder().name("Remove JSON Fields/Columns")
+ .description("Comma delimited list of columns that should be
removed when parsing JSON and building the CSV. " +
+ "This includes all top level and most granular nested
fields/columns. By default with nothing specified every field " +
+ "will be parsed.")
+ .required(false)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor EMPTY_FIELDS = new
PropertyDescriptor
+ .Builder().name("Empty field value")
+ .description("During denormalization/flattening of the JSON
the value that will be substituted for empty fields values " +
+ "(Example: NULL). Defaults to empty string if not
specified.")
+ .required(false)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor INCLUDE_HEADERS = new
PropertyDescriptor
+ .Builder().name("Include Headers")
+ .description("Whether or not to include headers in the CSV
output")
+ .required(true)
+ .allowableValues(INCLUDE_HEADER_TRUE, INCLUDE_HEADER_FALSE)
+ .defaultValue(INCLUDE_HEADER_TRUE.getValue())
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final Relationship RELATIONSHIP_SUCCESS = new
Relationship.Builder()
+ .name("success")
+ .description("Successfully parsing the JSON file to CSV ")
+ .build();
+
+ public static final Relationship RELATIONSHIP_FAILURE = new
Relationship.Builder()
+ .name("failure")
+ .description("Failed parsing the JSON file to CSV ")
+ .build();
+
--- End diff --
Should there be an "original" relationship that the JSON file would be
transferred to upon success? Other processors do similar things.
> Convert JSON format to CSV
> --------------------------
>
> Key: NIFI-1583
> URL: https://issues.apache.org/jira/browse/NIFI-1583
> Project: Apache NiFi
> Issue Type: Improvement
> Components: Core Framework
> Affects Versions: 0.4.1
> Reporter: Adis Cesir
> Priority: Minor
>
> Processor with the ability to flatten out multi nested JSON Objects and
> Arrays into tabular format / CSV. An example of a use for this is the common
> server responses and log events producing JSON which can be converted into
> fixed delimited structure to ingest into RDBMS,HDFS/Hive and any other system
> preferring 2 dimensional tabular formats.
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