Apache Sqoop documentation

Sqoop 2 Connector Development


Sqoop 2 Connector Development

This document describes how to implement a connector in the Sqoop 2 using the code sample from one of the built-in connectors ( GenericJdbcConnector ) as a reference. Sqoop 2 jobs support extraction from and/or loading to different data sources. Sqoop 2 connectors encapsulate the job lifecyle operations for extracting and/or loading data from and/or to different data sources. Each connector will primarily focus on a particular data source and its custom implementation for optimally reading and/or writing data in a distributed environment.

What is a Sqoop Connector?

Connectors provide the facility to interact with many data sources and thus can be used as a means to transfer data between them in Sqoop. The connector implementation will provide logic to read from and/or write to a data source that it represents. For instance the ( GenericJdbcConnector ) encapsulates the logic to read from and/or write to jdbc enabled relational data sources. The connector part that enables reading from a data source and transferring this data to internal Sqoop format is called the FROM and the part that enables writng data to a data source by transferring data from Sqoop format is called TO. In order to interact with these data sources, the connector will provide one or many config classes and input fields within it.

Broadly we support two main config types for connectors, link type represented by the enum ConfigType.LINK and job type represented by the enum ConfigType.JOB. Link config represents the properties to physically connect to the data source. Job config represent the properties that are required to invoke reading from and/or writing to particular dataset in the data source it connects to. If a connector supports both reading from and writing to, it will provide the FromJobConfig and ToJobConfig objects. Each of these config objects are custom to each connector and can have one or more inputs associated with each of the Link, FromJob and ToJob config types. Hence we call the connectors as configurables i.e an entity that can provide configs for interacting with the data source it represents. As the connectors evolve over time to support new features in their data sources, the configs and inputs will change as well. Thus the connector API also provides methods for upgrading the config and input names and data related to these data sources across different versions.

The connectors implement logic for various stages of the extract/load process using the connector API described below. While extracting/reading data from the data-source the main stages are Initializer, Partitioner, Extractor and Destroyer. While loading/writitng data to the data source the main stages currently supported are Initializer, Loader and Destroyer. Each stage has its unique set of responsibilities that are explained in detail below. Since connectors understand the internals of the data source they represent, they work in tandem with the sqoop supported execution engines such as MapReduce or Spark (in future) to accomplish this process in a most optimal way.

When do we add a new connector?

You add a new connector when you need to extract/read data from a new data source, or load/write data into a new data source that is not supported yet in Sqoop 2. In addition to the connector API, Sqoop 2 also has an submission and execution engine interface. At the moment the only supported engine is MapReduce, but we may support additional engines in the future such as Spark. Since many parallel execution engines are capable of reading/writing data, there may be a question of whether adding support for a new data source should be done through the connector or the execution engine API.

Our guideline are as follows: Connectors should manage all data extract(reading) from and/or load(writing) into a data source. Submission and execution engine together manage the job submission and execution life cycle to read/write data from/to data sources in the most optimal way possible. If you need to support a new data store and details of linking to it and don’t care how the process of reading/writing from/to happens then you are looking to add a connector and you should continue reading the below Connector API details to contribute new connectors to Sqoop 2.

Connector Implementation

The SqoopConnector class defines an API for the connectors that must be implemented by the connector developers. Each Connector must extend SqoopConnector and override the methods shown below.

public abstract String getVersion();
public abstract ResourceBundle getBundle(Locale locale);
public abstract Class getLinkConfigurationClass();
public abstract Class getJobConfigurationClass(Direction direction);
public abstract From getFrom();
public abstract To getTo();
public abstract ConnectorConfigurableUpgrader getConfigurableUpgrader()

Connectors can optionally override the following methods:

public List<Direction> getSupportedDirections();
public Class<? extends IntermediateDataFormat<?>> getIntermediateDataFormat()

The getVersion method returns the current version of the connector It is important to provide a unique identifier every time a connector jar is released externally. In case of the Sqoop built-in connectors, the version refers to the Sqoop build/release version. External connectors can also use the same or similar mechanism to set this version. The version number is critical for the connector upgrade logic used in Sqoop

 public String getVersion() {
  return VersionInfo.getBuildVersion();

The getFrom method returns From instance which is a Transferable entity that encapsulates the operations needed to read from the data source that the connector represents.

The getTo method returns To instance which is a Transferable entity that encapsulates the operations needed to write to the data source that the connector represents.

Methods such as getBundle , getLinkConfigurationClass , getJobConfigurationClass are related to Configurations

Since a connector represents a data source and it can support one of the two directions, either reading FROM its data source or writing to its data souurce or both, the getSupportedDirections method returns a list of directions that a connector will implement. This should be a subset of the values in the Direction enum we provide:

public List<Direction> getSupportedDirections() {
    return Arrays.asList(new Direction[]{


The getFrom method returns From instance which is a Transferable entity that encapsulates the operations needed to read from the data source the connector represents. The built-in GenericJdbcConnector defines From like this.

private static final From FROM = new From(

public From getFrom() {
  return FROM;

Initializer and Destroyer

Initializer is instantiated before the submission of sqoop job to the execution engine and doing preparations such as connecting to the data source, creating temporary tables or adding dependent jar files. Initializers are executed as the first step in the sqoop job lifecyle. Here is the Initializer API.

public abstract void initialize(InitializerContext context, LinkConfiguration linkConfiguration,
    JobConfiguration jobConfiguration);

public List<String> getJars(InitializerContext context, LinkConfiguration linkConfiguration,
    JobConfiguration jobConfiguration){
     return new LinkedList<String>();

public abstract Schema getSchema(InitializerContext context, LinkConfiguration linkConfiguration,
    JobConfiguration jobConfiguration) {
       return new NullSchema();

In addition to the initialize() method where the job execution preparation activities occur, the Initializer can also implement the getSchema() method for the directions FROM and TO that it supports.

The getSchema() method is used by the sqoop system to match the data extracted/read by the From instance of connector data source with the data loaded/written to the To instance of the connector data source. In case of a relational database or columnar database, the returned Schema object will include collection of columns with their data types. If the data source is schema-less, such as a file, a default NullSchema will be used (i.e a Schema object without any columns).

NOTE: Sqoop 2 currently does not support extract and load between two connectors that represent schema-less data sources. We expect that atleast the From instance of the connector or the To instance of the connector in the sqoop job will have a schema. If both From and To have a associated non empty schema, Sqoop 2 will load data by column name, i.e, data in column “A” in From instance of the connector for the job will be loaded to column “A” in the To instance of the connector for that job.

Destroyer is instantiated after the execution engine finishes its processing. It is the last step in the sqoop job lifecyle, so pending clean up tasks such as dropping temporary tables and closing connections. The term destroyer is a little misleading. It represents the phase where the final output commits to the data source can also happen in case of the TO instance of the connector code.


The Partitioner creates Partition instances ranging from 1..N. The N is driven by a configuration as well. The default set of partitions created is set to 10 in the sqoop code. Here is the Partitioner API

Partitioner must implement the getPartitions method in the Partitioner API.

public abstract List<Partition> getPartitions(PartitionerContext context,
    LinkConfiguration linkConfiguration, FromJobConfiguration jobConfiguration);

Partition instances are passed to Extractor as the argument of extract method. Extractor determines which portion of the data to extract by a given partition.

There is no actual convention for Partition classes other than being actually Writable and toString() -able. Here is the Partition API

public abstract class Partition {
  public abstract void readFields(DataInput in) throws IOException;
  public abstract void write(DataOutput out) throws IOException;
  public abstract String toString();

Connectors can implement custom Partition classes. GenericJdbcPartitioner is one such example. It returns the GenericJdbcPartition objects.


Extractor (E for ETL) extracts data from a given data source Extractor must implement the extract method in the Extractor API.

public abstract void extract(ExtractorContext context,
                             LinkConfiguration linkConfiguration,
                             JobConfiguration jobConfiguration,
                             SqoopPartition partition);

The extract method extracts data from the data source using the link and job configuration properties and writes it to the SqoopMapDataWriter (provided in the extractor context given to the extract method). The SqoopMapDataWriter has the SqoopWritable thats holds the data read from the data source in the Intermediate Data Format representation

Extractors use Writer’s provided by the ExtractorContext to send a record through the sqoop system.


The extractor must iterate through the given partition in the extract method.

while (resultSet.next()) {


The getTo method returns TO instance which is a Transferable entity that encapsulates the operations needed to wtite data to the data source the connector represents. The built-in GenericJdbcConnector defines To like this.

private static final To TO = new To(

public To getTo() {
  return TO;

Initializer and Destroyer

Initializer and Destroyer of a To instance are used in a similar way to those of a From instance. Refer to the previous section for more details.


A loader (L for ETL) receives data from the From instance of the sqoop connector associated with the sqoop job and then loads it to an TO instance of the connector associated with the same sqoop job

Loader must implement load method of the Loader API

public abstract void load(LoaderContext context,
                          ConnectionConfiguration connectionConfiguration,
                          JobConfiguration jobConfiguration) throws Exception;

The load method reads data from SqoopOutputFormatDataReader (provided in the loader context of the load methods). It reads the data in the Intermediate Data Format representation and loads it to the data source.

Loader must iterate in the load method until the data from DataReader is exhausted.

while ((array = context.getDataReader().readArrayRecord()) != null) {

NOTE: we do not yet support a stage for connector developers to control how to balance the loading/writitng of data across the mutiple loaders. In future we may be adding this to the connector API to have custom logic to balance the loading across multiple reducers.

Sqoop Connector Identifier : sqoopconnector.properties

Every Sqoop 2 connector needs to have a sqoopconnector.properties in the packaged jar to be identified by Sqoop. A typical sqoopconnector.properties for a sqoop2 connector looks like below

# Sqoop Foo Connector Properties
org.apache.sqoop.connector.class = org.apache.sqoop.connector.foo.FooConnector
org.apache.sqoop.connector.name = sqoop-foo-connector

If the above file does not exist, then Sqoop will not load this jar and thus cannot be registered into Sqoop repository for creating Sqoop jobs

Sqoop Connector Build-time Dependencies

Sqoop provides the connector-sdk module identified by the package:org.apache.sqoop.connector It provides the public facing apis for the external connectors to extend from. It also provides common utilities that the connectors can utilize for converting data to and from the sqoop intermediate data format

The common-test module identified by the package org.apache.sqoop.common.test provides utilities used related to the built-in connectors such as the JDBC, HDFS, and Kafka connectors that can be used by the external connectors for creating the end-end integration test for sqoop jobs

The test module identified by the package org.apache.sqoop.test provides various minicluster utilites the integration tests can extend from to run
a sqoop job with the given sqoop connector either using it as a FROM or TO data-source

Hence the pom.xml for the sqoop kite connector built using the kite-sdk might look something like below

  <!-- Sqoop modules -->

  <!-- Testing specified modules -->

  <!-- Connector required modules -->


Configurable registration

One of the currently supported configurable in Sqoop are the connectors. Sqoop 2 registers definitions of connectors from the file named sqoopconnector.properties which each connector implementation should provide to become available in Sqoop.

# Generic JDBC Connector Properties
org.apache.sqoop.connector.class = org.apache.sqoop.connector.jdbc.GenericJdbcConnector
org.apache.sqoop.connector.name = generic-jdbc-connector


Implementations of SqoopConnector overrides methods such as getLinkConfigurationClass and getJobConfigurationClass returning configuration class.

public Class getLinkConfigurationClass() {
  return LinkConfiguration.class;

public Class getJobConfigurationClass(Direction direction) {
  switch (direction) {
    case FROM:
      return FromJobConfiguration.class;
    case TO:
      return ToJobConfiguration.class;
      return null;

Configurations are represented by annotations defined in org.apache.sqoop.model package. Annotations such as ConfigurationClass , ConfigClass , Config and Input are provided for defining configuration objects for each connector.

@ConfigurationClass is a marker annotation for ConfigurationClasses that hold a group or lis of ConfigClasses annotated with the marker @ConfigClass

public class LinkConfiguration {

  @Config public LinkConfig linkConfig;

  public LinkConfiguration() {
    linkConfig = new LinkConfig();

Each ConfigClass defines the different inputs it exposes for the link and job configs. These inputs are annotated with @Input and the user will be asked to fill in when they create a sqoop job and choose to use this instance of the connector for either the From or To part of the job.

@ConfigClass(validators = {@Validator(LinkConfig.ConfigValidator.class)})
public class LinkConfig {
  @Input(size = 128, validators = {@Validator(NotEmpty.class), @Validator(ClassAvailable.class)} )
  @Input(size = 128) public String jdbcDriver;
  @Input(size = 128) public String connectionString;
  @Input(size = 40)  public String username;
  @Input(size = 40, sensitive = true) public String password;
  @Input public Map<String, String> jdbcProperties;

Each ConfigClass and the inputs within the configs annotated with Input can specifiy validators via the @Validator annotation described below.

Configs and Inputs

As discussed above, Input provides a way to express the type of config parameter exposed. In addition it allows connector developer to add attributes that describe how the input will be used in the sqoop job. Here are the list of the supported attributes

Inputs associated with the link configuration include:

Attribute Type Description Example
size Integer Describes the maximum size of the attribute value . @Input(size = 128) public String driver
sensitive Boolean Describes if the input value should be hidden from display @Input(sensitive = true) public String password
editable Enum Describes the roles that can edit the value of this input @Input(editable = ANY) public String value
overrides String Describes a list of other inputs this input can override in this config @Input(overrides =”value”) public String lvalue

Editable Attribute: Possible values for the Enum InputEditable are USER_ONLY, CONNECTOR_ONLY, ANY. If an input says editable by USER_ONLY, then the connector code during the job run or upgrade cannot update the config input value. Similarly for a CONNECTOR_ONLY, user cannot update its value via the rest api or shell command line.

Overrides Attribute: USER_ONLY input attribute values cannot be overriden by other inputs.

Empty Configuration

If a connector does not have any configuration inputs to specify for the ConfigType.LINK or ConfigType.JOB it is recommended to return the EmptyConfiguration class in the getLinkConfigurationClass() or getJobConfigurationClass(..) methods.

public class EmptyConfiguration { }

Configuration ResourceBundle

The config and its corresponding input names, the input field description are represented in the config resource bundle defined per connector.

# jdbc driver
connection.jdbcDriver.label = JDBC Driver Class
connection.jdbcDriver.help = Enter the fully qualified class name of the JDBC \
                   driver that will be used for establishing this connection.

# connect string
connection.connectionString.label = JDBC Connection String
connection.connectionString.help = Enter the value of JDBC connection string to be \
                   used by this connector for creating connections.


Those resources are loaded by getBundle method of the SqoopConnector.

public ResourceBundle getBundle(Locale locale) {
  return ResourceBundle.getBundle(
  GenericJdbcConnectorConstants.RESOURCE_BUNDLE_NAME, locale);

Validations for Configs and Inputs

Validators validate the config objects and the inputs associated with the config objects. For config objects themselves we encourage developers to write custom valdiators for both the link and job config types.

@Input(size = 128, validators = {@Validator(value = StartsWith.class, strArg = "jdbc:")} )

@Input(size = 255, validators = { @Validator(NotEmpty.class) })

Sqoop 2 provides a list of standard input validators that can be used by different connectors for the link and job type configuration inputs.

public class NotEmpty extends AbstractValidator<String> {
public void validate(String instance) {
  if (instance == null || instance.isEmpty()) {
   addMessage(Status.ERROR, "Can't be null nor empty");

The validation logic is executed when users creating the sqoop jobs input values for the link and job configs associated with the From and To instances of the connectors associated with the job.

Loading External Connectors

Loading new connector say sqoop-foo-connector to the sqoop2, here are the steps to follow

  1. Create a sqoop-foo-connector.jar. Make sure the jar contains the sqoopconnector.properties for it to be picked up by Sqoop
  2. Add this jar to the a folder on your installation machine and update the path to this folder in the sqoop.properties located under the server/conf directory under the Sqoop2 for the key org.apache.sqoop.connector.external.loadpath
# External connectors load path
# "/path/to/external/connectors/": Add all the connector JARs in the specified folder
  1. Start the Sqoop 2 server and while initializing the server this jar should be loaded into the Sqoop 2’s class path and registered into the Sqoop 2 repository

Sqoop 2 MapReduce Job Execution Lifecycle with Connector API

Sqoop 2 provides MapReduce utilities such as SqoopMapper and SqoopReducer that aid sqoop job execution.

Note: Any class prefixed with Sqoop is a internal sqoop class provided for MapReduce and is not part of the conenector API. These internal classes work with the custom implementations of Extractor, Partitioner in the From instance and Loader in the To instance of the connector.

When reading from a data source, the Extractor provided by the From instance of the connector extracts data from a corresponding data source it represents and the Loader, provided by the TO instance of the connector, loads data into the data source it represents.

The diagram below describes the initialization phase of a job. SqoopInputFormat create splits using Partitioner.

    |SqoopInputFormat|          |Partitioner|
    `-------+--------'          `-----+-----'
 getSplits  |                         |
            |      getPartitions      |
            |                         |         ,---------.
            |                         |-------> |Partition|
            |                         |         `----+----'
            |                         |              |          ,----------.
            |                         |              |          `----+-----'

The diagram below describes the map phase of a job. SqoopMapper invokes From connector’s extractor’s extract method.

   run    |
--------->|                                   ,------------------.
          |                                   `------+-----------'
          |                ,---------.               |
          |--------------> |Extractor|               |
          |                `----+----'               |
          |      extract        |                    |
          |                     |                    |
         read from Data Source  |                    |
          |                     |                    |---------->|SqoopWritable|
          |                     |                    |                |
          |                     |                    |                |  context.write(writable, ..)

The diagram below decribes the reduce phase of a job. OutputFormat invokes To connector’s loader’s load method (via SqoopOutputFormatLoadExecutor ).

  |SqoopReducer|  |SqoopNullOutputFormat|
      |                 |-> |SqoopOutputFormatLoadExecutor|
      |                 |                  |                             |
      |                 |                  |-> |SqoopRecordWriter|-->|SqoopWritable|
    getRecordWriter     |                  |   `--------+--------'   `---+---------'
----------------------->| getRecordWriter  |            |                |
      |                 |----------------->|            |                |     ,--------------.
      |                 |                  |            |                |     `------+-------'
      |                 |<- - - - - - - - -|            |                |            |    ,------.
<- - - - - - - - - - - -|                  |            |                |            |--->|Loader|
      |                 |                  |            |                |            |    `--+---'
      |                 |                  |            |                |            |       |
      |                 |                  |            |                |            | load  |
 run  |                 |                  |            |                |            |------>|
----->|                 |     write        |            |                |            |       |
      |                 |                  |            |--------------->| getContent |<------|
      |                 |                  |            |                |            | - - ->|
      |                 |                  |            |                |            |       | write into Data Source

More details can be found in Sqoop MR Execution Engine