Github user rickysaltzer commented on a diff in the pull request:
https://github.com/apache/nifi/pull/2020#discussion_r130412143
--- Diff:
nifi-nar-bundles/nifi-kudu-bundle/nifi-kudu-processors/src/main/java/org/apache/nifi/processors/kudu/PutKudu.java
---
@@ -0,0 +1,120 @@
+/*
+ * 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.kudu;
+
+import org.apache.kudu.Schema;
+import org.apache.kudu.Type;
+import org.apache.kudu.client.Insert;
+import org.apache.kudu.client.PartialRow;
+import org.apache.kudu.client.KuduTable;
+
+import org.apache.nifi.annotation.behavior.EventDriven;
+import org.apache.nifi.annotation.behavior.InputRequirement;
+import org.apache.nifi.annotation.behavior.SupportsBatching;
+import org.apache.nifi.annotation.documentation.CapabilityDescription;
+import org.apache.nifi.annotation.documentation.Tags;
+import org.apache.nifi.components.PropertyDescriptor;
+import org.apache.nifi.processor.Relationship;
+import org.apache.nifi.serialization.record.Record;
+
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
+
+@EventDriven
+@SupportsBatching
+@InputRequirement(InputRequirement.Requirement.INPUT_REQUIRED)
+@Tags({"put", "database", "NoSQL", "kudu", "HDFS"})
+@CapabilityDescription("Reads records from an incoming FlowFile using the
provided Record Reader, and writes those records " +
+ "to the specified Kudu's table. The schema for the table must be
provided in the processor properties or from your source." +
+ " If any error occurs while reading records from the input, or
writing records to Kudu, the FlowFile will be routed to failure")
+
+public class PutKudu extends AbstractKudu {
+
+ @Override
+ protected List<PropertyDescriptor> getSupportedPropertyDescriptors() {
+ final List<PropertyDescriptor> properties = new ArrayList<>();
+ properties.add(KUDU_MASTERS);
+ properties.add(TABLE_NAME);
+ properties.add(SKIP_HEAD_LINE);
+ properties.add(RECORD_READER);
+
+ return properties;
+ }
+
+ @Override
+ public Set<Relationship> getRelationships() {
+ final Set<Relationship> rels = new HashSet<>();
+ rels.add(REL_SUCCESS);
+ rels.add(REL_FAILURE);
+ return rels;
+ }
+
+ @Override
+ protected Insert insertRecordToKudu(KuduTable kuduTable, Record
record, List<String> fieldNames) throws IllegalStateException, Exception {
+ Insert insert = kuduTable.newInsert();
+ PartialRow row = insert.getRow();
+ Schema colSchema = kuduTable.getSchema();
+
+ for (String colName : fieldNames) {
+ int colIdx = this.getColumnIndex(colSchema, colName);
+ if (colIdx != -1) {
+ Type colType =
colSchema.getColumnByIndex(colIdx).getType();
+
+ switch (colType.getDataType()) {
+ case BOOL:
+ row.addBoolean(colIdx,
record.getAsBoolean(colName));
+ break;
+ case FLOAT:
+ row.addFloat(colIdx, record.getAsFloat(colName));
+ break;
+ case DOUBLE:
+ row.addDouble(colIdx, record.getAsDouble(colName));
+ break;
+ case BINARY:
+ row.addBinary(colIdx,
record.getAsString(colName).getBytes());
+ break;
+ case INT8:
+ case INT16:
--- End diff --
You can cast it from `int` to `short` before calling `addShort(..)`. If the
user is using an `int` field to store a value inclusive of a `short` range then
it's safe to cast. If the user is storing something outside the range of a
`short` then an `Exception` will be thrown. I think this is a better approach
since it allows users to utilize the `INT8` and `INT16` column types if they
are able to guarantee that they're in contract with those value ranges.
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