Some time ago I wrote a very simple SQL interpreter for Javascript for fun one weekend and have since started using it in production in a few projects for work, and as requirements change for things I'm working on, I implement new features in the library. For a year or so I've made due with a single, monstrous function that handled lexing, parsing and interpreting all at once, all while avoiding regex as much as possible as I've gotten the impression that regex is to be avoided as a parsing tool.

I'm now learning the hard way that this is not sustainable. I'm attempting to implement a proper lexer/parser before adding any new features.


As someone with no experience writing a real lexer I started by reading a bunch of really dry tutorials in languages I don't really understand. The one thing they all seemed to have in common is that they check each character of the input string individually, which to me, seems tedious and unnecessary, so I decided to try it my own way, which turned out to be much, much simpler and shorter than implementations I found online.

If my implementation is so much better then why aren't other people doing something similar? There must be something wrong with this algorithm, what is it?

My Method

  1. Have an array of Regex patterns that matches each token. Patterns are ordered by priority, for example, quoted strings come before numbers because numbers that are quoted are strings, not numbers.
  2. Loop thru each pattern and produce an array of arrays which contain all matches for every token (in the same order of priority). Each match contains:
    • The literal text that was matched
    • Its position in the input string
    • The type of token it matches (eg STRING or NUMBER)
  3. Loop thru each token match and string them together when one match begins exactly where another one ends, in order of priority.
  4. When a match is not found at the position where the last match ended check to see if length of all matched tokens === the length of the input string. If not, throw an error.

The Code

This demo will tokenize a string and show you the details for each token when you mouseover the word or symbol.

function jSQLLexer(input) {
	this.input = input;
	this.pos = 0;
	this.real_pos = 0;
	this.tokens = [];
	this.token_matches = [];

// Get all possible token matches to be sorted out
jSQLLexer.prototype.getTokenMatches = function(){
	if(this.token_matches.length) return this.token_matches;
	this.token_matches = []
	var r;
	for(var i=0; i<jSQLLexer.token_types.length; i++){
		this.token_matches[i] = [];
		while ((r = jSQLLexer.token_types[i].pattern.exec(this.input)) != null) {
	return this.token_matches;

// Get list of tokens for the input string
jSQLLexer.prototype.getTokens = function(){	
	if(this.tokens.length) return this.tokens;
	this.pos = 0;
	var matches = this.getTokenMatches(),
	throwaway = ["COMMENT", "WHITESPACE"];
	for(var type_id=0; type_id<matches.length; type_id++){
		if(this.pos >= this.input.length) break;
		for(var match_index=0; match_index<matches[type_id].length; match_index++){
			var r = matches[type_id][match_index];
			if(r.index !== this.pos) continue;
			var token = new jSQLToken(this.pos, r[0], type_id);
			this.pos += token.length;
			if(throwaway.indexOf(token.type) === -1) this.tokens.push(token);
	if(this.pos !== this.input.length){
		var pos;
			var lastToken = this.tokens[this.tokens.length-1];
			pos = lastToken.input_pos + lastToken.length;
		}else pos = 0;
		throw new jSQL_Lexer_Error(pos, this.input); 
	return this.tokens;

jSQLLexer.token_types = [
	{pattern: /"(?:[^"\\]|\\.)*"/g,
		type: 'STRING',
		name: "DQ STRING"},
	{pattern: /'(?:[^'\\]|\\.)*'/g,
		type: 'STRING',
		name: "SQ STRING"},

	{pattern: /--.*[\n\r$]/g,
		type: 'COMMENT',
	{pattern: /\/\*([\s\S]*?)\*\//g,
		type: 'COMMENT',

	{pattern: /\r?\n|\r/g,
		type: 'WHITESPACE',
		name: "LINEBREAK"},
	{pattern: /[ \t]/g,
		type: 'WHITESPACE',
		name: "WHITESPACE"},

	{pattern: /\d+/g,
		type: 'NUMBER',
		name: 'INTEGER'},
	{pattern: /\d+.\.\d+/g,
		type: 'NUMBER',
		name: 'FLOAT'},

	{pattern: /if not exists/gi,
		type: 'QUALIFIER',
		name: "IF NOT EXISTS"},

	{pattern: /!=/gi,
		type: 'SYMBOL',
		name: "NOT EQUAL"},
	{pattern: /<>/gi,
		type: 'SYMBOL',
		name: "NOT EQUAL"},
	{pattern: /\(/gi,
		type: 'SYMBOL',
		name: "LEFT PEREN"},
	{pattern: /\)/gi,
		type: 'SYMBOL',
		name: "RIGHT PEREN"},
	{pattern: /,/gi,
		type: 'SYMBOL',
		name: "COMMA"},
	{pattern: /\?/gi,
		type: 'SYMBOL',
		name: "QUESTION MARK"},
	{pattern: /,/gi,
		type: 'SYMBOL',
		name: "COMMA"},
	{pattern: /\*/gi,
		type: 'SYMBOL',
		name: "ASTERISK"},
	{pattern: /;/gi,
		type: 'SYMBOL',
		name: "SEMICOLON"},
	{pattern: /=/gi,
		type: 'SYMBOL',
		name: "EQUALS"},
	{pattern: />/gi,
		type: 'SYMBOL',
		name: "GREATER THAN"},
	{pattern: /</gi,
		type: 'SYMBOL',
		name: "LESS THAN"},

	{pattern: /primary key/gi,
		type: 'KEYWORD',
		name: "PRIMARY KEY"},
	{pattern: /unique key/gi,
		type: 'KEYWORD',
		name: "UNIQUE KEY"},
	{pattern: /values/gi,
		type: 'KEYWORD',
		name: "VALUES"},
	{pattern: /from/gi,
		type: 'KEYWORD',
		name: "FROM"},
	{pattern: /auto_increment/gi,
		type: 'KEYWORD',
		name: "AUTO_INCREMENT"},
	{pattern: /ignore/gi,
		type: 'KEYWORD',
		name: "IGNORE"},
	{pattern: /into/gi,
		type: 'KEYWORD',
		name: "INTO"},
	{pattern: /all/gi,
		type: 'KEYWORD',
		name: "ALL"},
	{pattern: /distinct/gi,
		type: 'KEYWORD',
		name: "DISTINCT"},
	{pattern: /distinctrow/gi,
		type: 'KEYWORD',
		name: "DISTINCTROW"},
	{pattern: /where/gi,
		type: 'KEYWORD',
		name: "WHERE"},
	{pattern: /and/gi,
		type: 'KEYWORD',
		name: "AND"},
	{pattern: /like/gi,
		type: 'KEYWORD',
		name: "LIKE"},
	{pattern: /order by/gi,
		type: 'KEYWORD',
		name: "ORDER BY"},
	{pattern: /or/gi,
		type: 'KEYWORD',
		name: "OR"},
	{pattern: /limit/gi,
		type: 'KEYWORD',
		name: "LIMIT"},
	{pattern: /offset/gi,
		type: 'KEYWORD',
		name: "OFFSET"},
	{pattern: /asc/gi,
		type: 'KEYWORD',
		name: "ASC"},
	{pattern: /desc/gi,
		type: 'KEYWORD',
		name: "DESC"},
	{pattern: /set/gi,
		type: 'KEYWORD',
		name: "SET"},

	{pattern: /create table/gi,
		type: 'DIRECTIVE',
		name: "CREATE TABLE"},
	{pattern: /insert/gi,
		type: 'DIRECTIVE',
		name: "INSERT"},
	{pattern: /delete from/gi,
		type: 'DIRECTIVE',
		name: "DELETE FROM"},
	{pattern: /drop table/gi,
		type: 'DIRECTIVE',
		name: "DROP TABLE"},
	{pattern: /update/gi,
		type: 'DIRECTIVE',
		name: "UPDATE"},
	{pattern: /select/gi,
		type: 'DIRECTIVE',
		name: "SELECT"},

	// IDENTIFIERs are developer specified so should be checked last
	{pattern: /`[0-9a-zA-Z$_]*[0-9a-zA-Z$_]`/gi,
		type: 'IDENTIFIER',
		name: "QTD IDENTIFIER"},
	{pattern: /[0-9a-zA-Z$_]*[0-9a-zA-Z$_]/gi,
		type: 'IDENTIFIER',

// This is a polyfill required by jSQLToken
var jSQL = {
	types: {
  	exists: type=>-1<[

// The token constructor
function jSQLToken(pos, literal, tok_index){
	this.type_id = tok_index;
	this.input_pos = pos;
	this.literal = literal;
	this.value = literal;
	this.length = literal.length;
	this.type = jSQLLexer.token_types[tok_index].type;
	this.name = jSQLLexer.token_types[tok_index].name;
	if(this.type === "IDENTIFIER" && this.name === "UNQTD IDENTIFIER" && jSQL.types.exists(this.literal)) 
		this.name = "DATA TYPE";
	if(this.type === "IDENTIFIER" && this.name === "QTD IDENTIFIER")
		this.value = literal.replace(/`/g,'');
	if(this.type === "STRING" && this.name === "DQ STRING")
		this.value = literal.substr(1, literal.length - 2).replace(/\"/g, '"');
	if(this.type === "STRING" && this.name === "SQ STRING")
		this.value = literal.substr(1, literal.length - 2).replace(/\'/g, "'");
	if(this.type === "NUMBER") this.value = parseFloat(this.literal);

function jSQL_Lexer_Error(pos, context) {
	var max_ellipse_len = 25;
	var ellipse_len = context.length > pos + max_ellipse_len ? max_ellipse_len :
		context.length - pos;
	var preview = context.substr(pos, ellipse_len);
	this.error = "0070";
	this.message = "Unknown token near char "+pos+" of "+context.length+" \""+preview+"\".";
	this.stack = undefined;
	var e = new Error();
	if(e.stack) this.stack = e.stack;
	this.toString = function () {
		return "jSQL Lexer Error #"+this.error+" - "+this.message;

const drawOutput = sql => {
	let tokens = new jSQLLexer(sql).getTokens(), output=[];
  tokens.forEach((token,i)=>output.push("<span class='token' data-token-id='"+i+"'>"+token.literal+"</span>"));
  output.push("<div id=o></div>");
  $("body").html(output.join(" "));
     let o = [];
      for(let i in tokens[$(this).data("token-id")])
        if(["string", "number"].indexOf(typeof tokens[$(this).data("token-id")][i]) > -1)
        o.push("<b>"+i+"</b> = "+tokens[$(this).data("token-id")][i]);
  	$(this).css({color: "red"});
  	$(this).css({color: "black"});

drawOutput(`CREATE TABLE IF NOT EXISTS someTable (
  name varchar(3),
  numba2 smallint(3),
  numba3 mediumint(3),
  numba4 bigint(3), 
  type enum('type1', "type2", "type3")
<script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js"></script>

  • \$\begingroup\$ You might want to take a look at jison \$\endgroup\$
    – rici
    Oct 26, 2017 at 12:16
  • \$\begingroup\$ Thanks for the link @rici. I've seen Jison, but this is more or less a learning thing for me which is why I'm building everything from scratch. I feel like if I'm gonna use Jison I might as well just use SQL.js like other similar libraries. I might just end up going that route eventually though. \$\endgroup\$ Oct 26, 2017 at 13:31
  • \$\begingroup\$ Your choice obviously. If you want to learn how to parse (to be able to write parsers for different syntaxes), then learning how to use standard tools makes sense. If you want to learn how parsing algorithms work, read a good book :-). (Grune is my fave.) Implementing a parsing algo is an interesting exercise, certainly, but it is like implementing a Taylor series instead of using exp(): it undoubtedly teaches you a lot but does it give you any insight at all about programming problems which involve exponentiation? \$\endgroup\$
    – rici
    Oct 26, 2017 at 13:51

1 Answer 1


I have implemented several lexers, mostly in C. Since the C language doesn't have regular expressions, and since regular expression engines need to evaluate the string character-by-character anyhow, checking each character by hand makes sense in C. This is probably why tutorials like this approach.

Even in C, though, there are tools for writing lexers using regular expressions. The input looks looks something like this:

  some_regex { /* code to handle the some_regex */ },
  [0-9]+     { /* code to handle numbers */ },
  [a-zA-Z]+  { /* code to handle words */ }
  // etc...

Each time the resulting lexer matches a complete regular expression, it calls the associated block of code. This is nice, because the lexer can evaluate all the possibilites in parallel. If it recieves the character 's', for example, both the some_regex and [a-zA-Z] cases are in the running. If the next character is anything but 'o', that eliminates some_regex, and only the [a-zA-Z] case remains. So, this approach can be incredibly efficient by considering all possibilities at once.

If I were to write a lexer in Javascript using regular expressions, I would probably try to replicate the structure above. Starting at the beginning of the string, I would test each of my regular expressions one-at-a-time until I found one that fits the beginning of the string. Then I would save the match, advance forward in the string, and repeat.

You algorithm is basically the opposite of this - you try all the regular expressions over the entire input string, and then try to string the matches together. So, your approach probably has about the same code complexity as the more traditional approach. It's not clear whether your approach would be faster or slower, since yours produces more garbage for the GC, while the more traditional approach involves more manual string slicing (in your approach, RegExp.exec does the slicing).

Since both garbage collection and string copying are expensive, Javascript lexers that focus on performance tend to use the character-by-character approach. It's harder to write than regexp-based approaches, for sure, but lexing is frequently a big bottleneck in real systems, so it's often worth the investment. It doesn't sound like your project is performance-critical, so your approach is probably fine.

  • \$\begingroup\$ No, definitely not performance critical. It's fine as is for now, just trying to wrap my head around why this was so much simpler. i'm definitely not doing it char by char (manually) in a language where size matters as well. Not worth the investment for now. I like what you said about checking the patterns one by one instead of all at once, at least that will get rid of the garbage. Thanks for answering! \$\endgroup\$ Oct 25, 2017 at 22:32
  • 1
    \$\begingroup\$ The difference between C/C++ and JS is that in JS the RegExp code is native compiled, while JS string manipulation is in compiled JS manipulating the String Object (16bit unicode). That makes JS if (str[c] === "A") {... significantly (an order of magnitude) slower than C if (*(str + c) == 'A') {... In javascript using RegExp for string searches is by far quicker than the char by char approch. Though that said you can get a performance increase if you use TypedArray, and str len < (2^31) -1 with a 1 of cost converting String to Uint8Array. But still slower than RegExp. \$\endgroup\$
    – Blindman67
    Oct 27, 2017 at 12:05
  • 1
    \$\begingroup\$ The code str[c] === "A" has to slice out and compare a one-character string. That's slow. The fast approach is more like str.charCodeAt(c) === 101, which works on numbers (101 is the ASCII code for A). This would have the same performance as a Uint8Array, but without copying anything. It obviously sucks to build, though. I can't think of a way to write a lexer using regexes that doesn't involve String.slice or equivalent. It there was a "test a RegEp starting at an arbitrary string offset" primitive, then regexes would make more sense. \$\endgroup\$ Oct 28, 2017 at 0:08

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