Druid VS Antlr4

DRUID VS ANTLR4

测试方法

环境：x86_64，eclipse kepler，jdk 6
测试对象：antlr v4，druid手写sql parser模块
测试过程：分别采用单线程、多线程并发测试。单线程时，比较antlr、druid各自解析1次同一条sql语句的性能；多线程(50线程)时，比较antlr、druid所有线程完成1次同一条sql解析的性能。

测试结果##

类别	单线程(druid比antlr)	多线程(druid比antlr)
简单select	7倍	6倍
复杂select	约200倍	约1600倍
Insert	6倍	11倍
Update	15倍	13倍
Delete	3倍	4倍

总结##

1、性能：druid好于antlr。
2、语法支持：两者皆可实现各类语法，但antlr易于druid实现。目前发现druid没有完全实现pg语法，如int ‘123’类型转换。
3、可维护性：antlr好于druid 特别是体现在新增语法时，修改druid的工作量大于antlr。
4、可读性：antlr好于druid antlr采用独立的语法文件管理语法规则，druid语法规则与代码耦合。
5、关键字支持：两者皆支持。druid需要使用switch语句块穷举。

---

package com.laudandjolynn.test;

import java.text.NumberFormat;
import java.util.concurrent.Callable;
import java.util.concurrent.CompletionService;
import java.util.concurrent.ExecutorCompletionService;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

import org.apache.commons.cli.BasicParser;
import org.apache.commons.cli.CommandLine;
import org.apache.commons.cli.CommandLineParser;
import org.apache.commons.cli.Options;

import com.alibaba.druid.sql.dialect.postgresql.parser.PGSQLStatementParser;
import com.laudandjolynn.idb.AntlrParser;

public class SqlParser {
	private final static String ANTLR = "ANTLR";
	private final static String DRUID = "DRUID";

	public static void main(String[] args) throws Exception {
		CommandLineParser clp = new BasicParser();
		Options options = new Options();
		options.addOption("t", true, "");
		options.addOption("m", true, "");
		options.addOption("p", true, "");
		options.addOption("s", true, "");
		CommandLine cl = clp.parse(options, args);
		String helpMsg = "usage: java -jar test.jar -t {antlr|druid} [-m times] [-p threads] -s sql";
		if (!cl.hasOption('t') || !cl.hasOption('s')) {
			System.out.println(helpMsg);
			System.exit(0);
		}

		String tool = cl.getOptionValue('t');
		String sql = cl.getOptionValue('s');
		int threadCount = cl.hasOption('p') ? Integer.valueOf(cl
				.getOptionValue('p')) : 1;
		int executeTimes = cl.hasOption('m') ? Integer.valueOf(cl
				.getOptionValue('m')) : 1;
		if (threadCount == 1) {
			single(1, sql, tool, false);
			single(executeTimes, sql, tool, true);
		} else {
			multiple(1, sql, tool, 1, false);
			multiple(executeTimes, sql, tool, threadCount, true);
		}
		System.exit(0);
	}

	private static void single(int executeTimes, String sql, String tool,
			boolean stat) {
		long sum = 0;
		long max = Long.MIN_VALUE;
		long min = Long.MAX_VALUE;
		int maxIndex = -1;
		for (int j = 0; j < executeTimes; j++) {
			long start = System.nanoTime();
			parse(sql, tool);
			long elapse = System.nanoTime() - start;
			if (max < elapse) {
				max = elapse;
				maxIndex = j;
			}
			if (min > elapse) {
				min = elapse;
			}
			sum += elapse;
		}
		if (stat) {
			NumberFormat format = NumberFormat.getInstance();
			format.setMaximumFractionDigits(3);
			System.out.println("max: " + format.format(max / 1000000.0)
					+ " ms. max value index: " + maxIndex);
			System.out
					.println("min: " + format.format(min / 1000000.0) + " ms");
			System.out.println("avg: "
					+ format.format(sum / (double) executeTimes / 1000000.0)
					+ " ms");
		}
	}

	private static void multiple(int executeTimes, String sql, String tool,
			int threadCount, boolean stat) throws Exception {
		ExecutorService executorService = Executors
				.newFixedThreadPool(threadCount);
		CompletionService<Long[]> completionService = new ExecutorCompletionService<Long[]>(
				executorService);
		for (int i = 0; i < threadCount; i++) {
			completionService.submit(new Parser(executeTimes, sql, tool));
		}

		long sum = 0;
		long max = Long.MIN_VALUE;
		long min = Long.MAX_VALUE;
		int maxIndex = -1;
		for (int i = 0; i < threadCount; i++) {
			Long[] elapses = completionService.take().get();
			for (int j = 0; j < executeTimes; j++) {
				if (max < elapses[j]) {
					max = elapses[j];
					maxIndex = i * j;
				}
				if (min > elapses[j]) {
					min = elapses[j];
				}
				sum += elapses[j];
			}
		}

		if (stat) {
			NumberFormat format = NumberFormat.getInstance();
			format.setMaximumFractionDigits(3);
			System.out.println("max: " + format.format(max / 1000000.0)
					+ " ms. max value index: " + maxIndex);
			System.out
					.println("min: " + format.format(min / 1000000.0) + " ms");
			System.out.println("avg: "
					+ format.format(sum / executeTimes / threadCount
							/ 1000000.0) + " ms");
		}
	}

	private static class Parser implements Callable<Long[]> {
		private String sql = null;
		private String tool = null;
		private int executeTimes;

		public Parser(int executeTimes, String sql, String tool) {
			this.executeTimes = executeTimes;
			this.sql = sql;
			this.tool = tool;
		}

		@Override
		public Long[] call() throws Exception {
			Long result[] = new Long[executeTimes];
			for (int i = 0; i < executeTimes; i++) {
				long start = System.nanoTime();
				parse(sql, tool);
				result[i] = System.nanoTime() - start;
			}
			return result;
		}
	}

	private static void parse(String sql, String tool) {
		if (ANTLR.equalsIgnoreCase(tool)) {
			AntlrParser.parse(sql);
		} else if (DRUID.equalsIgnoreCase(tool)) {
			new PGSQLStatementParser(sql).parseStatement();
		}
	}
}