The parsers are the flagship part of Compose and power extremely advanced autocompletes and other SQL functionalities. They are running on the client side and comes with just a few megabytes of JavaScript that are cached by the browser. This provides a very reactive experience to the end user and allows to import them as classic JavaScript modules for your own development needs.
While the dynamic content like the list of tables, columns is obviously fetched via remote endpoints, all the SQL knowledge of the statements is available.
The main dialects are:
But there are more! See all the currently shipped SQL dialects.
This guide takes you through the steps necessary to create an autocompleter for any SQL dialect. The major benefits are:
Looking at quick code examples?
There are several parsers in Compose already (e.g. one for Impala, one for Hive..) and a generic SQL that is used for other dialects. The parsers are written using a bison grammar and are generated with jison. They are 100% Javascript and live on the client side, this gives the performance of a desktop editor in your browser.
Building a dedicated work is more effort but it then allows a very rich end user experience, e.g.:
Note: Tree-sitter is also a new promising error tolerant parser, but that would be a lot of work to convert the jison grammar to it, but worth mentioning for inspiration.
Normally parsers generate a parse tree but for our purposes we don’t really care about the statement itself but rather about what should happen when parts of a particular statement is encountered. During parsing the state is kept outside the parse tree and in case of syntax errors this enables us to provide some results up to the point of the error. There are two ways that incomplete/erroneous statements are handled, first we try to define most of the incomplete grammar and secondly we rely on the “error” token which allows the parser to recover.
The parsers provide one function, parseSql, that accepts the text before the cursor and the text after the cursor as arguments. The function returns an object containing instructions on what to suggest given the input.
As an example:
sqlParserRepository.getAutocompleteParser('impala').then(parser => {
console.log(parser.parseSql('SELECT * FROM customers'));
});
Would output something like:
{
definitions: [],
locations: (6) [{…}, {…}, {…}, {…}, {…}, {…}],
lowerCase: false,
suggestAggregateFunctions: {tables: [Array(1)]},
suggestAnalyticFunctions: true,
suggestColumns: {source: "select", tables: [{identifierChain: [{name: "customers"}]}]},
suggestFunctions: {},
suggestKeywords: (8) [{…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}]
}
We take this output and link it to various sources of metadata to provide the list of suggestions the user finally sees. In this case we’d use the data from “suggestColumns” to call the backend for all the columns of the “customers” table. We’d also use the functions library to list all the UDFs etc.
Here’s a list of some of the different types of suggestions the parser can identify:
suggestAggregateFunctions
suggestAnalyticFunctions
suggestColRefKeywords
suggestColumnAliases
suggestColumns
suggestCommonTableExpressions
suggestDatabases
suggestFilters
suggestFunctions
suggestGroupBys suggestHdfs
suggestIdentifiers
suggestJoinConditions
suggestJoins
suggestKeywords
suggestOrderBys
suggestSetOptions
suggestTables
suggestValues
Parsers are generated and added to the repository using the command generateParsers.js under tools/jison/. To for instance generate all the Impala parsers you would run the following command in the hue folder:
cd tools/jison
node generateParsers.js impala
In reality two parsers are generated per dialect, one for syntax and one for autocomplete. The syntax parsers is a subset of the autocomplete parser with no error recovery and without the autocomplete specific grammar.
All the jison grammar files can be found here and the generated parsers are also committed together with their tests here.
Parsers are sharing a maximum of the common syntax via some modules so that it is easy to improve the specificness of any of them while not starting from sratch.
e.g. in structure.json:
{
"lexer": "sql.jisonlex",
"autocomplete": [
"../generic/autocomplete_header.jison",
"abort/abort_transactions.jison",
"common/table_constraint.jison",
"alter/alter_common.jison",
"alter/alter_database.jison",
"alter/alter_index.jison",
"alter/alter_materialized_view.jison",
"alter/alter_table.jison",
"alter/alter_view.jison",
"analyze/analyze_table.jison",
...
],
"syntax": [
"../generic/syntax_header.jison",
"abort/abort_transactions.jison",
"common/table_constraint.jison",
"alter/alter_common.jison",
"alter/alter_database.jison",
"alter/alter_index.jison",
"alter/alter_materialized_view.jison",
...
]
}
In a regular SQL parser you might define the grammar of a select statement like this:
SelectStatement
: 'SELECT' ColumnList 'FROM' Identifier
;
ColumnList
: Identifier
| ColumnList ',' Identifier
;
This would be able to parse a statement like ‘SELECT a, b, c FROM some_table’ (depending on lexer definitions of course).
To turn this into an autocompleter we add the notion of a cursor. Often, the user has the cursor somewhere in the statement. In the previous section, we were assuming that the query was already typed and the user had not mouse cursor within it.
The cursor is represented as an obscure character that is unlikely to be used in a statement. Currently ‘\u2020’ was picked, the dagger, identified as ‘CURSOR’ in the lexer. The actual parsed string is therefore beforeCursor + ‘\u2020’ + afterCursor.
For the statement above we’d add an extra rule with an _EDIT postfix like this:
SelectStatement
: 'SELECT' ColumnList 'FROM' Identifier
;
SelectStatement_EDIT
: 'CURSOR' --> { suggestKeywords: ['SELECT'] }
| 'SELECT' ColumnList_EDIT
| 'SELECT' ColumnList 'CURSOR' --> { suggestKeywords: ['FROM'] }
| 'SELECT' ColumnList 'FROM' 'CURSOR' --> { suggestTables: {} }
| 'SELECT' ColumnList_EDIT 'FROM' Identifier --> { suggestColumns: { table: $4 } }
;
So for example if a cursor without any text is encountered, it will tell us to suggest the ‘SELECT’ keyword etc.
The extra space is just for the documentation to show the complete output with locations, it should indeed be clarified a bit. The reason for the extra space is that the parser ignores partial words, consider the following where | denotes the cursor:
SELECT * FROM som|
The parser will treat this as “SELECT * FROM |” and it leaves it up to the editor logic to filter any tables, starting with “som”.
The goal is to create from scratch a new parser for the PostgreSQL database.
Make sure you have jison installed and a development Hue. Then configure a PostgreSQL interpreter.
In the Hue folder:
./build/env/bin/pip install psycopg2-binary
and edit your hue config desktop/conf/pseudo-distributed.ini to contain:
[notebook]
[[interpreters]]
[[[postgresql]]]
name = postgresql
interface=sqlalchemy
options='{"url": "postgresql://hue:hue@localhost:31335/hue"}'
Our generateParsers tool can take an existing dialect and setup the source code for a new parsers based on that.
In the hue folder run:
cd tools/jison
yarn
node generateParsers.js -new generic postgresql
After the -new argument you specify an existing dialect to clone first and then the name of the new parser.
Once executed the tool has cloned the generic parser with tests and generated a new postgresql parsers. The jison files can be found under js/parse/jison/sql/postgresql/ and the testscan be found in js/parse/sql/postgresql/test.
To regenerate the parsers after changes to the jison files run:
cd tools/jison
node generateParsers.js postgresql
The tool will report any problems with the grammar. Note that it might still generate a parser if the grammar isn’t ambiguous but it’s likely that there will be test failures.
This gives you an idea on how to add custom syntax to the newly generated postgresql parser. For this example we’ll add the REINDEX statement as it’s quite simple.
REINDEX { INDEX | TABLE | DATABASE | SYSTEM } name [ FORCE ]
We’ll start by adding a test, in postgresqlAutocompleteParser.test.js in the test folder inside the main describe function before the first it('should...:
describe('REINDEX', () => {
it('should handle "REINDEX TABLE foo FORCE; |"', () => {
assertAutoComplete({
beforeCursor: 'REINDEX TABLE foo FORCE; ',
afterCursor: '',
noErrors: true,
containsKeywords: ['SELECT'],
expectedResult: {
lowerCase: false
}
});
});
it('should suggest keywords for "REINDEX |"', () => {
assertAutoComplete({
beforeCursor: 'REINDEX ',
afterCursor: '',
noErrors: true,
containsKeywords: ['INDEX', 'DATABASE'],
expectedResult: {
lowerCase: false
}
});
});
});
When we now run yarn test -- postgresqlAutocompleteParser.test.js there should be two failing tests.
Alternatively, if using Jest directly and working on parsers currently being skipped in the CI, provide matching file names and an empty blacklist file pattern. e.g.:
jest calciteAutocompleteParser.Select.stream.test.js --testPathIgnorePatterns=[]
jest calciteAutocompleteParser --testPathIgnorePatterns=[]
Next we’ll have to add the keyword to the lexer, let’s open sql.jisonlex in the jison folder for postgresql and add the following new tokens:
'REINDEX' { parser.determineCase(yytext); return 'REINDEX'; }
'INDEX' { return 'INDEX'; }
'SYSTEM' { return 'SYSTEM'; }
'FORCE' { return 'FORCE'; }
Now let’s add the grammar, starting with the complete specification. For simplicity we’ll add it in sql_main.jison, at the bottom of the file add:
DataDefinition
: ReindexStatement
;
ReindexStatement
: 'REINDEX' ReindexTarget RegularOrBacktickedIdentifier OptionalForce
;
ReindexTarget
: 'INDEX'
| 'TABLE'
| 'DATABASE'
| 'SYSTEM'
;
OptionalForce
:
| 'FORCE'
;
“DataDefinition” is an existing rule and this extends that rule with “ReindexStatement”.
Save the files and first run node tools/jison/generateParsers.js postgresql then yarn test -- postgresqlAutocompleteParser.test.js and we should be down to one failing test.
For the next one we’ll add some keyword suggestions after the user has typed REINDEX, we’ll continue below the ReindexStatement in sql_main.jison:
DataDefinition_EDIT
: ReindexStatement_EDIT
;
ReindexStatement_EDIT
: 'REINDEX' 'CURSOR'
{
parser.suggestKeywords(['DATABASE', 'INDEX', 'SYSTEM', 'TABLE']);
}
;
Again, run cd tools/jison/; node generateParsers.js postgresql then yarn test -- postgresqlAutocompleteParser.test.js and the tests should both be green.
We also want the autocompleter to suggest the keyword REINDEX when the user hasn’t typed anything, to do that let’s first add the following test with the other new ones in postgresqlAutocompleteParser.test.js:
it('should suggest REINDEX for "|"', () => {
assertAutoComplete({
beforeCursor: '',
afterCursor: '',
noErrors: true,
containsKeywords: ['REINDEX'],
expectedResult: {
lowerCase: false
}
});
});
For this to pass we need to add REINDEX to the list of DDL and DML keywords in the file sqlParseSupport.js next to the generated parser (js/parse/sql/postgresql/sqlParseSupport.js/). Find the function parser.suggestDdlAndDmlKeywords and add ‘REINDEX’ to the keywords array. Now run yarn test -- postgresqlAutocompleteParser.test.js and the three tests should pass.
Before you continue further, note that in this case there will be two new failing tests where the keyword ‘REINDEX’ has to be added.
In order to use the newly generated parsers we have to add them to the webpack bundles:
yarn webpack
yarn webpack-workers
While developing it will speed up if the webpack bundling runs in the background, for this open two terminal sessions and run yarn dev in one and yarn dev-workers in the other. It will then monitor changes to the files and build a lot quicker.
After the bundling you can now test it directly in the editor!