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/*
* 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.zeppelin.spark;
import org.apache.commons.lang.StringUtils;
import org.apache.spark.SparkContext;
import org.apache.spark.scheduler.SparkListener;
import org.apache.spark.scheduler.SparkListenerJobStart;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.catalyst.expressions.GenericRow;
import org.apache.spark.sql.types.StructType;
import org.apache.zeppelin.interpreter.InterpreterContext;
import org.apache.zeppelin.interpreter.ResultMessages;
import org.apache.zeppelin.interpreter.SingleRowInterpreterResult;
import org.apache.zeppelin.tabledata.TableDataUtils;
import java.util.ArrayList;
import java.util.List;
import java.util.Properties;
public class Spark3Shims extends SparkShims {
private SparkSession sparkSession;
public Spark3Shims(Properties properties, Object entryPoint) {
super(properties);
this.sparkSession = (SparkSession) entryPoint;
}
public void setupSparkListener(final String master,
final String sparkWebUrl,
final InterpreterContext context) {
SparkContext sc = SparkContext.getOrCreate();
sc.addSparkListener(new SparkListener() {
@Override
public void onJobStart(SparkListenerJobStart jobStart) {
if (sc.getConf().getBoolean("spark.ui.enabled", true) &&
!Boolean.parseBoolean(properties.getProperty("zeppelin.spark.ui.hidden", "false"))) {
buildSparkJobUrl(master, sparkWebUrl, jobStart.jobId(), jobStart.properties(), context);
}
}
});
}
@Override
public String showDataFrame(Object obj, int maxResult, InterpreterContext context) {
if (obj instanceof Dataset) {
Dataset<Row> df = ((Dataset) obj).toDF();
String[] columns = df.columns();
// DDL will empty DataFrame
if (columns.length == 0) {
return "";
}
// fetch maxResult+1 rows so that we can check whether it is larger than zeppelin.spark.maxResult
List<Row> rows = df.takeAsList(maxResult + 1);
String template = context.getLocalProperties().get("template");
if (!StringUtils.isBlank(template)) {
if (rows.size() >= 1) {
return new SingleRowInterpreterResult(sparkRowToList(rows.get(0)), template, context).toHtml();
} else {
return "";
}
}
StringBuilder msg = new StringBuilder();
msg.append("%table ");
msg.append(StringUtils.join(TableDataUtils.normalizeColumns(columns), "\t"));
msg.append("\n");
boolean isLargerThanMaxResult = rows.size() > maxResult;
if (isLargerThanMaxResult) {
rows = rows.subList(0, maxResult);
}
for (Row row : rows) {
for (int i = 0; i < row.size(); ++i) {
msg.append(TableDataUtils.normalizeColumn(row.get(i)));
if (i != row.size() -1) {
msg.append("\t");
}
}
msg.append("\n");
}
if (isLargerThanMaxResult) {
msg.append("\n");
msg.append(ResultMessages.getExceedsLimitRowsMessage(maxResult, "zeppelin.spark.maxResult"));
}
// append %text at the end, otherwise the following output will be put in table as well.
msg.append("\n%text ");
return msg.toString();
} else {
return obj.toString();
}
}
private List sparkRowToList(Row row) {
List list = new ArrayList();
for (int i = 0; i< row.size(); i++) {
list.add(row.get(i));
}
return list;
}
@Override
public Dataset<Row> getAsDataFrame(String value) {
String[] lines = value.split("\\n");
String head = lines[0];
String[] columns = head.split("\t");
StructType schema = new StructType();
for (String column : columns) {
schema = schema.add(column, "String");
}
List<Row> rows = new ArrayList<>();
for (int i = 1; i < lines.length; ++i) {
String[] tokens = lines[i].split("\t");
Row row = new GenericRow(tokens);
rows.add(row);
}
return sparkSession.createDataFrame(rows, schema);
}
}