@apla/clickhouse

Database interface for http://clickhouse.yandex

npm install @apla/clickhouse

Synopsis

var ch = new ClickHouse ({host: clickhouse.host, port: 8123, auth: "user:password"});
// or
var ch = new ClickHouse (clickhouse.host);

// do the query, callback interface, not recommended for selects
ch.query ("CREATE DATABASE clickhouse_test", function (err, data) {

});

// promise interface (requires 'util.promisify' for node < 8, Promise shim for node < 4)
ch.querying ("CREATE DATABASE clickhouse_test").then (…);

// it is better to use stream interface to fetch select results
var stream = ch.query ("SELECT 1");

// or collect records yourself
var rows = [];

stream.on ('metadata', function (columns) {
  // do something with column list
});

stream.on ('data', function (row) {
  rows.push (row);
});

stream.on ('error', function (err) {
  // TODO: handler error
});

stream.on ('end', function () {
  // all rows are collected, let's verify count
  assert (rows.length === stream.supplemental.rows);
  // how many rows in result are set without windowing:
  console.log ('rows in result set', stream.supplemental.rows_before_limit_at_least);
});

// insert from file

var tsvStream = fs.createReadStream ('data.tsv');
var clickhouseStream = clickHouse.query (statement, {inputFormat: 'TSV'});

tsvStream.pipe (clickhouseStream);

// insert row data
var clickhouseStream = clickHouse.query (statement, {inputFormat: 'TSV'}, function (err) {

  console.log ('Insert complete!');

});

// data will be formatted for you
clickhouseStream.write ([1, 2.22, "erbgwerg", new Date ()]);

// prepare data yourself
clickhouseStream.write ("1\t2.22\terbgwerg\t2017-07-17 17:17:17");

clickhouse.end ();

API

new ClickHouse (options)

var options = {
  host: "clickhouse.msk",
  queryOptions: {
    profile: "web",
    database: "test"
  },
  omitFormat: false
};

var clickHouse = new ClickHouse (options);

If you provide options as a string, they are assumed as a host parameter in connection options

Connection options (accept all options documented for http.request):

• auth: authentication as user:password, optional
• host: host to connect, can contain port name
• pathname: pathname of ClickHouse server or / if omited,

queryOptions object can contain any option from Settings (docs: en ru )

For example:

• database: default database name to lookup tables etc.
• profile: settings profile to use
• readonly: don't allow to change data
• max_rows_to_read: self explanatory

Driver options:

• dataObjects: use FORMAT JSON instead of FORMAT JSONCompact for output. By default (false), you'll receive array of values for each row. If you set dataObjects to true, every row will become an object with format: {fieldName: fieldValue, …}
• format: this is format for data loading with INSERT statements.
• syncParser: collect data, then parse entire response. Should be faster, but for large datasets all your dataset goes into memory (actually, entire response + entire dataset). Default: false
• omitFormat: FORMAT JSONCompact will be added by default to every query which returns dataset. Currently SELECT|SHOW|DESC|DESCRIBE|EXISTS\s+TABLE. You can change this behaviour by providing this option. In this case you should add FORMAT JSONCompact by yourself. Should be detected automatically. Default false;

var stream = clickHouse.query (statement, [options], [callback])

Query sends a statement to a server

Stream is a regular nodejs object stream, it can be piped to process records.

Stream events:

• metadata: when a column information is parsed,
• data: when a row is available,
• error: something is wrong,
• end: when entire response is processed

After response is processed, you can read a supplemental response data, such as row count via stream.supplemental.

Options are the same for query and constructor excluding connection.

Callback is optional and will be called upon completion with a standard node (error, result) signature.

You should have at least one error handler listening. Via callbacks or via stream errors. If you have callback and stream listener, you'll have error notification in both listeners.

clickHouse.querying (statement, [options]).then (…)

Promise interface. Similar to the callback one.

clickHouse.ping (function (err, response) {})

Sends an empty query and check if it "Ok.\n"

clickHouse.pinging ().then (…)

Promise interface for ping

Notes

Bulk data loading with INSERT statements

INSERT can be used for bulk data loading. There is a 2 formats easily implementable with javascript: CSV and TabSeparated/TSV.

CSV is useful for loading from file, thus you can read and pipe into clickhouse file contents. To activate CSV parsing you should set inputFormat option to CSV for driver or query (BEWARE: not works as expected, use TSV):

var csvStream = fs.createReadStream ('data.csv');
var clickhouseStream = clickHouse.query (statement, {inputFormat: CSV});

csvStream.pipe (clickhouseStream);

TSV is useful for loading from file and bulk loading from external sources, such as other databases. Only \\, \t and \n need to be escaped in strings; numbers, nulls, bools and date objects need some minor processing. You can send prepared TSV data strings (line ending will be appended automatically), buffers (always passed as is) or Arrays with fields.

Internally, every field will be converted to the format which ClickHouse can accept. Then escaped and joined with delimiter for the particular format. If you ever need to store rows (in arrays) and send preformatted data, you can do it.

ClickHouse also supports JSONEachRow format which can be useful to insert javascript objects if you have such recordset.

Memory size

You can read all the records into memory in single call like this:

var ch = new ClickHouse ({host: host, port: port});
ch.query ("SELECT number FROM system.numbers LIMIT 10", {syncParser: true}, function (err, result) {
  // result will contain all the data you need
});

In this case whole JSON response from the server will be read into memory, then parsed into memory hogging your CPU. Default parser will parse server response line by line and emits events. This is slower, but much more memory and CPU efficient for larger datasets.

Promise interface

Promise interface have some restrictions. It is not recommended to use this interface for INSERT and SELECT queries. For the INSERT you cannot bulk load data via stream, SELECT will collect all the records in the memory. For simple usage where data size is controlled it is ok.