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Matthieu Monsch edited this page Jan 2, 2017 · 44 revisions

Types

What is a Type?

Each Avro type maps to a corresponding JavaScript Type:

  • int maps to IntType.
  • arrays map to ArrayTypes.
  • records map to RecordTypes.
  • etc.

An instance of a Type knows how to decode and encode its corresponding values. For example the StringType knows how to handle JavaScript strings:

const stringType = new avro.types.StringType();
const buf = stringType.toBuffer('Hi'); // Buffer containing 'Hi''s Avro encoding.
const str = stringType.fromBuffer(buf); // === 'Hi'

The toBuffer and fromBuffer methods above are convenience functions which encode and decode a single object into/from a standalone buffer.

Each type also provides a variety of other methods. Here are a few (refer to the API documentation for the full list):

  • JSON-encoding:

    const jsonString = type.toString('Hi'); // === '"Hi"'
const str = type.fromString(jsonString); // === 'Hi'

  • Validity checks:

    const b1 = stringType.isValid('hello'); // === true ('hello' is a valid string.)
const b2 = stringType.isValid(-2); // === false (-2 is not.)

  • Random object generation:

    const s = stringType.random(); // A random string.

How do I get a Type?

It is possible to instantiate types directly by calling their constructors (available in the avro.types namespace; this is what we used earlier), but in the vast majority of use-cases they will be automatically generated by parsing an existing schema.

avsc exposes a static method, Type.forSchema, to do the heavy lifting and generate a type from its Avro schema definition:

// Equivalent to what we did earlier.
const stringType = avro.Type.forSchema('string');

// A slightly more complex type.
const mapType = avro.Type.forSchema({type: 'map', values: 'long'});

// The sky is the limit!
const personType = avro.Type.forSchema({
  name: 'Person',
  type: 'record',
  fields: [
    {name: 'name', type: 'string'},
    {name: 'phone', type: ['null', 'string'], default: null},
    {name: 'address', type: {
      name: 'Address',
      type: 'record',
      fields: [
        {name: 'city', type: 'string'},
        {name: 'zip', type: 'int'}
      ]
    }}
  ]
});

Of course, all the type methods are available. For example:

personType.isValid({
  name: 'Ann',
  phone: null,
  address: {city: 'Cambridge', zip: 02139}
}); // === true

personType.isValid({
  name: 'Bob',
  phone: {string: '617-000-1234'},
  address: {city: 'Boston'}
}); // === false (Missing the zip code.)

For advanced use-cases, Type.forSchema also has a few options which are detailed the API documentation.

What about Avro files?

Avro files (meaning Avro object container files) hold serialized Avro records along with their schema. Reading them is as simple as calling createFileDecoder:

const personStream = avro.createFileDecoder('./persons.avro');

personStream is a readable stream of decoded records, which we can for example use as follows:

personStream.on('data', function (person) {
  if (person.address.city === 'San Francisco') {
    doSomethingWith(person);
  }
});

In case we need the records' type or the file's codec, they are available by listening to the 'metadata' event:

personStream.on('metadata', function (type, codec) { /* Something useful. */ });

To access a file's header synchronously, there also exists an extractFileHeader method:

const header = avro.extractFileHeader('persons.avro');

Writing to an Avro container file is possible using createFileEncoder:

const encoder = avro.createFileEncoder('./processed.avro', type);

Next steps

The API documentation provides a comprehensive list of available functions and their options. The Advanced usage section goes through a few examples to show how the API can be used, including remote procedure calls.

Services

Using Avro's RPC interface, we can implement portable and "type-safe" APIs:

  • Clients and servers can be implemented once and reused for many different communication protocols (in-memory, TCP, HTTP, etc.).
  • All data that flows through the API is automatically validated using its corresponding schema.

In this section, we'll walk through an example of building a simple link management service similar to bitly.

Defining a service

The first step to creating a service is to define its API or "protocol": the available calls and their signature. There are a couple ways of defining protocols; we can write JSON definitions directly, or we can define them using Avro's IDL (which can then be compiled to JSON definitions). The latter is typically more convenient so we will use this here.

/** A simple service to shorten URLs. */
protocol LinkService {

  /** Map a URL to an alias, returns true if successful. */
  boolean createAlias(string alias, string url);

  /** Expand an alias, returning null if the alias doesn't exist. */
  union { null, string } expandAlias(string alias);
}

Server implementation

// The protocol generated from the above declaration (see the sample code for
// the complete snippet).
let protocol;

// In this example, we'll use a simple map as URL cache.
const cache = new Map();

// We now instantiate a server corresponding to our API and implement both
// calls.
const server = avro.Service.forProtocol(protocol)
  .createServer()
  .onCreateAlias(function (alias, url, cb) {
    if (cache.has(alias)) {
      cb(null, false); // The alias already exists, return false.
    } else {
      cache.set(alias, url); // Add the alias to the cache.
      cb(null, true);
    }
  })
  .onExpandAlias(function (alias, cb) {
    cb(null, cache.get(alias) || null);
  });

Calling our service.

TODO

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