Node-parquet

Parquet is a columnar storage format available to any project in the Hadoop ecosystem. This nodejs module provides native bindings to the parquet functions from parquet-cpp.

A pure javascript parquet format driver (still in development) is also provided.

Build, install

The native c++ module has the following dependencies which must be installed before attempting to build:

• Linux:
  • g++ and gcc version >= 4.8
  • cmake > 2.8.6
  • boost
  • bison
  • flex
• MacOSX:
  • Xcode (at least command line tools)
  • boost (brew install boost)
• MS-Windows: not supported (contributions welcome)

Note that you need also python2 and c++/make toolchain for building NodeJS native addons.

The standard way of building and installing, provided that above depencies are met, is simply to run:

npm build

From 0.2.4 version, a command line tool called parquet is provided. It can be installed globally by running npm install -g. Note that if you install node-parquet this way, you can still use it as a dependency module in your local projects by linking (npm link node-parquet) which avoids the cost of recompiling the complete parquet-cpp library and its dependencies.

Otherwise, for developers to build directly from a github clone:

git clone https://github.com/mvertes/node-parquet.git
cd node-parquet
git submodule update --init --recursive
npm install [-g]

After install, the parquet-cpp build directory build_deps can be removed by running npm run clean, recovering all disk space taken for building parquet-cpp and its dependencies.

Usage

Command line tool

A command line tool parquet is provided. It's quite minimalist right now and needs to be improved:

Usage: parquet [options] <command> [<args>]

Command line tool to manipulate parquet files

Commands:
  cat file       Print file content on standard output
  head file      Print the first lines of file
  info file      Print file metadata

Options:
  -h,--help      Print this help text
  -V,--version   Print version and exits

Reading

The following example shows how to read a parquet file:

var parquet = require('node-parquet');

var reader = new parquet.ParquetReader('my_file.parquet');
console.log(reader.info());
console.log(reader.rows();
reader.close();

Writing

The following example shows how to write a parquet file:

var parquet = require('node-parquet');

var schema = {
  small_int: {type: 'int32', optional: true},
  big_int: {type: 'int64'},
  my_boolean: {type: 'bool'},
  name: {type: 'byte_array', optional: true},
};

var data = [
  [ 1, 23234, true, 'hello world'],
  [  , 1234, false, ],
];

var writer = new parquet.ParquetWriter('my_file.parquet', schema);
writer.write(data);
writer.close();

API reference

The API is not yet considered stable nor complete.

To use this module, one must require('node-parquet')

Class: parquet.ParquetReader

ParquetReader object performs read operations on a file in parquet format.

new parquet.ParquetReader(filename)

Construct a new parquet reader object.

• filename: String containing the parquet file path

Example:

const parquet = require('node-parquet');
const reader = new parquet.ParquetReader('./parquet_cpp_example.parquet');

reader.close()

Close the reader object.

reader.info()

Return an Object containing parquet file metadata. The object looks like:

{
  version: 0,
  createdBy: 'Apache parquet-cpp',
  rowGroups: 1,
  columns: 8,
  rows: 500
}

reader.read(column_number)

This is a low level function, it should not be used directly.

Read and return the next element in the column indicated by column_number.

In the case of a non-nested column, a basic value (Boolean, Number, String or Buffer) is returned, otherwise, an array of 3 elemnents is returned, where a[0] is the parquet definition level, a[1] the parquet repetition level, and a[2] the basic value. Definition and repetition levels are useful to reconstruct rows of composite, possibly sparse records with nested columns.

• column_number: the column number in the row

reader.rows([nb_rows])

Return an Array of rows, where each row is itself an Array of column elements.

• nb_rows: Number defining the maximum number of rows to return.

Class: parquet.ParquetWriter

ParquetWriter object implements write operation on a parquet file.

new parquet.ParquetWriter(filename, schema, [compression])

Construct a new parquet writer object.

• filename: String containing the parquet file path
• schema: Object defining the data structure, where keys are column names and values are Objects with the following fields:
  • "type": required String indicating the type of column data, can be any of:
    • "bool": boolean value, converted from Boolean
    • "int32": 32 bits integer value, converted from Number
    • "int64": 64 bits integer value, converted from Number
    • "timestamp": 64 bits integer value, converted from Date, with parquet logical type TIMESTAMP_MILLIS, the number of milliseconds from the Unix epoch, 00:00:00.000 on 1 January 1970, UTC
    • "float": 32 bits floating number value, converted from Number
    • "double": 64 bits floating number value, converted from Number
    • "byte_array": array of bytes, converted from a String or buffer
    • "string": array of bytes, converted from a String, with parquet logical type UTF8
    • "group": array of nested structures, described with a "schema" field
  • "optional": Boolean indicating if the field can be omitted in a record. Default: false.
  • "repeated": Boolean indicating if the field can be repeated in a record, thus forming an array. Ignored if not defined within a schema of type "group" (schema itself or one of its parent).
  • "schema": Object which content is a schema defining the nested structure. Required for objects where type is "group", ignored for others.
• compression: optional String indicating the compression algorithm to apply to columns. Can be one of "snappy", "gzip", "brotli" or "lzo". By default compression is disabled.

For example, considering the following object: { name: "foo", content: [ 1, 2, 3] }, its descriptor schema is:

const schema = {
  name: { type: "string" },
  content: {
    type: "group",
    repeated: "true",
    schema: { i0: { type: "int32" } }
  }
};

writer.close()

Close a file opened for writing. Calling this method explicitely before exiting is mandatory to ensure that memory content is correctly written in the file.

writer.writeSync(rows)

Write the content of rows in the file opened by the writer. Data from rows will be dispatched into the separate parquet columns according to the schema specified in the contructor.

• rows: Array of rows, where each row is itself an Array of column elements, according to the schema.

For example, considering the above nested schema, a write operation could be:

writer.write([
  [ "foo", [ 1, 2, 3] ],
  [ "bar", [ 100, 400, 600, 2 ] ]
]);

Caveats and limitations

• no schema extract at reading yet
• int64 bigger than 2^53 - 1 are not represented accurately (big number library like bignum integration planned)
• purejs implementation not complete, although most of metadata is now correctly parsed.
• read and write are only synchronous
• the native library parquet-cpp does not build on MS-Windows
• many tests are missing
• benchmarks are missing
• neat commmand line tool missing (one provided since 0.2.4)

Plan is to improve this over time. Contributions are welcome.

Building native extensions

From a macOS machine:

$ sh build-mac.sh
$ sh build-linux-docker.sh

This creates the release/linux and release/mac folders.

License

Apache-2.0