Github user paul-rogers commented on a diff in the pull request:
https://github.com/apache/drill/pull/1114#discussion_r167132068
--- Diff:
exec/java-exec/src/main/java/org/apache/drill/exec/store/log/LogRecordReader.java
---
@@ -0,0 +1,261 @@
+package org.apache.drill.exec.store.log;
+
+/*
+ * 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.
+ */
+
+import io.netty.buffer.DrillBuf;
+import org.apache.drill.common.exceptions.ExecutionSetupException;
+import org.apache.drill.common.exceptions.UserException;
+import org.apache.drill.common.expression.SchemaPath;
+import org.apache.drill.exec.exception.OutOfMemoryException;
+import org.apache.drill.exec.ops.FragmentContext;
+import org.apache.drill.exec.ops.OperatorContext;
+import org.apache.drill.exec.physical.impl.OutputMutator;
+import org.apache.drill.exec.store.AbstractRecordReader;
+import org.apache.drill.exec.store.dfs.DrillFileSystem;
+import org.apache.drill.exec.vector.complex.impl.VectorContainerWriter;
+import org.apache.drill.exec.vector.complex.writer.BaseWriter;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FSDataInputStream;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.io.compress.CompressionCodec;
+import org.apache.hadoop.io.compress.CompressionCodecFactory;
+import org.apache.hadoop.io.compress.CompressionInputStream;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.text.ParseException;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+public class LogRecordReader extends AbstractRecordReader {
+
+ private static final org.slf4j.Logger logger =
org.slf4j.LoggerFactory.getLogger(LogRecordReader.class);
+ private static final int MAX_RECORDS_PER_BATCH = 8096;
+
+ private String inputPath;
+ private BufferedReader reader;
+ private DrillBuf buffer;
+ private VectorContainerWriter writer;
+ private LogFormatPlugin.LogFormatConfig config;
+ private int lineCount;
+ private Pattern r;
+
+ private List<String> fieldNames;
+ private List<String> dataTypes;
+ private boolean errorOnMismatch;
+ private String dateFormat;
+ private String timeFormat;
+ private java.text.DateFormat df;
+ private java.text.DateFormat tf;
+ private long time;
+
+ public LogRecordReader(FragmentContext fragmentContext, String
inputPath, DrillFileSystem fileSystem,
+ List<SchemaPath> columns,
LogFormatPlugin.LogFormatConfig config) throws OutOfMemoryException {
+ try {
+ Path hdfsPath = new Path(inputPath);
+ Configuration conf = new Configuration();
+ FSDataInputStream fsStream = fileSystem.open(hdfsPath);
+ CompressionCodecFactory factory = new CompressionCodecFactory(conf);
+ CompressionCodec codec = factory.getCodec(hdfsPath);
+ if (codec == null) {
+ reader = new BufferedReader(new
InputStreamReader(fsStream.getWrappedStream(), "UTF-8"));
+ } else {
+ CompressionInputStream comInputStream =
codec.createInputStream(fsStream.getWrappedStream());
+ reader = new BufferedReader(new InputStreamReader(comInputStream));
+ }
+ this.inputPath = inputPath;
+ this.lineCount = 0;
+ this.config = config;
+ this.buffer = fragmentContext.getManagedBuffer(4096);
+ setColumns(columns);
+
+ } catch (IOException e) {
+ logger.debug("Log Reader Plugin: " + e.getMessage());
+ }
+ }
+
+ public void setup(final OperatorContext context, final OutputMutator
output) throws ExecutionSetupException {
+ this.writer = new VectorContainerWriter(output);
+ String regex = config.getPattern();
+
+
+ fieldNames = config.getFieldNames();
+ dataTypes = config.getDataTypes();
+ dateFormat = config.getDateFormat();
+ timeFormat = config.getTimeFormat();
+ errorOnMismatch = config.getErrorOnMismatch();
+
+ /*
+ This section will check for;
+ 1. Empty regex
+ 2. Invalid Regex
+ 3. Empty date string if the date format is used
+ 4. No capturing groups in the regex
+ 5. Incorrect number of data types
+ 6. Invalid data types
+ */
+ if (regex.isEmpty()) {
+ throw UserException.parseError().message("Log parser requires a
valid, non-empty regex in the plugin configuration").build(logger);
+ } else {
+ //TODO Check for invalid regex
+ r = Pattern.compile(regex);
+ Matcher m = r.matcher("test");
+ if (m.groupCount() == 0) {
+ throw UserException.parseError().message("Invalid Regular
Expression: No Capturing Groups", 0).build(logger);
+ } else if (m.groupCount() != (fieldNames.size())) {
+ throw UserException.parseError().message("Invalid Regular
Expression: Field names do not match capturing groups. There are " +
m.groupCount() + " captured groups in the data and " + fieldNames.size() + "
specified in the configuration.", 0).build(logger);
+
+ } else if ((dataTypes == null) || m.groupCount() !=
dataTypes.size()) {
+ //If the number of data types is not correct, create a list of
varchar
+ dataTypes = new ArrayList<String>();
+ for (int i = -0; i < m.groupCount(); i++) {
+ dataTypes.add("VARCHAR");
+ }
+ }
+ }
+
+ //Check and set up date formats
+ if (dataTypes.contains("DATE") || dataTypes.contains("TIMESTAMP")) {
+ if (dateFormat != null && !dateFormat.isEmpty()) {
+ df = new java.text.SimpleDateFormat(dateFormat);
+ } else {
+ throw UserException.parseError().message("Invalid date format.
The date formatting string was empty. Please specify a valid date format
string in the configuration for this data source.", 0).build(logger);
+ }
+ }
+
+ if (dataTypes.contains("TIME")) {
+ if (timeFormat != null && !timeFormat.isEmpty()) {
+ tf = new java.text.SimpleDateFormat(timeFormat);
+ } else {
+ throw UserException.parseError().message("Invalid time format.
The time formatting string was empty. Please specify a valid time format
string in the configuration for this data source.", 0).build(logger);
+ }
+ }
+
+ }
+
+ public int next() {
+ this.writer.allocate();
+ this.writer.reset();
+
+ int recordCount = 0;
+
+ try {
+ BaseWriter.MapWriter map = this.writer.rootAsMap();
+ String line = null;
+
+ while (recordCount < MAX_RECORDS_PER_BATCH && (line =
this.reader.readLine()) != null) {
+ lineCount++;
+
+ // Skip empty lines
+ if (line.trim().length() == 0) {
+ continue;
+ }
+
+ this.writer.setPosition(recordCount);
+ map.start();
+
+ Matcher m = r.matcher(line);
+ if (m.find()) {
+ for (int i = 1; i <= m.groupCount(); i++) {
+
+ String fieldName = fieldNames.get(i - 1);
+ String type = dataTypes.get(i - 1);
+ String fieldValue;
+
+ fieldValue = m.group(i);
+
+ if (fieldValue == null) {
+ fieldValue = "";
+ }
+
+ if (type.toUpperCase().equals("INT") ||
type.toUpperCase().equals("INTEGER")) {
+
map.integer(fieldName).writeInt(Integer.parseInt(fieldValue));
+ } else if (type.toUpperCase().equals("DOUBLE") ||
type.toUpperCase().equals("FLOAT8")) {
--- End diff --
Even better. This is an inner loop. Presumably we want it to go fast (which
is why it is deeply nested.)
So, rather than doing (slow) string compares (you could have used a
`switch` statement instead), in the `setup()` method, map names to ordinals:
`MinorType.ordinal()`. Then do a `switch` on the resulting numbers using, say,
`MinorType.VARCHAR.ordinal()`. Much faster.
---
