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# 1 Getting Started with Oracle Big Data Connectors

This chapter describes the Oracle Big Data Connectors, provides installation instructions, and identifies the permissions needed for users to access the connectors.

This chapter contains the following sections:

- About Oracle Big Data Connectors

- Big Data Concepts and Technologies

- Downloading the Oracle Big Data Connectors Software

- Oracle SQL Connector for Hadoop Distributed File System Setup

- Oracle Loader for Hadoop Setup

- Oracle Data Integrator Application Adapter for Hadoop Setup

- Oracle R Connector for Hadoop Setup

## 1.1 About Oracle Big Data Connectors

Oracle Big Data Connectors facilitate data access between data stored in a Hadoop cluster and Oracle Database. They can be licensed for use on either Oracle Big Data Appliance or a Hadoop cluster running on commodity hardware.

These are the connectors:

- Oracle SQL Connector for Hadoop Distributed File System (previously Oracle Direct Connector for HDFS): Enables an Oracle external table to access data stored in Hadoop Distributed File System (HDFS) files or a Hive table. The data can remain in HDFS or the Hive table, or it can be loaded into an Oracle database. Oracle SQL Connector for HDFS is a command-line utility that accepts generic command line arguments supported by the org.apache.hadoop.util.Tool interface. It also provides a preprocessor for Oracle external tables.

- Oracle Loader for Hadoop: Provides an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. Oracle Loader for Hadoop prepartitions the data if necessary and transforms it into a database-ready format. It optionally sorts records by primary key or user-defined columns before loading the data or creating output files. Oracle Loader for Hadoop is a MapReduce application that is invoked as a command-line utility. It accepts the generic command-line options that are supported by the org.apache.hadoop.util.Tool interface.

- Oracle Data Integrator Application Adapter for Hadoop: Extracts, transforms, and loads data from a Hadoop cluster into tables in an Oracle database, as defined using a graphical user interface.

- Oracle R Connector for Hadoop: Provides an interface between a local R environment, Oracle Database, and Hadoop, allowing speed-of-thought, interactive analysis on all three platforms. Oracle R Connector for Hadoop is designed to work independently, but if the enterprise data for your analysis is also stored in Oracle Database, then the full power of this connector is achieved when it is used with Oracle R Enterprise.

Individual connectors may require that software components be installed in Oracle Database and the Hadoop cluster. Users may also need additional access privileges in Oracle Database.

See Also:

My Oracle Support Information Center: Big Data Connectors (ID 1487399.2) and its related information centers.

## 1.2 Big Data Concepts and Technologies

Enterprises are seeing large amounts of data coming from multiple sources. Click-stream data in web logs, GPS tracking information, data from retail operations, sensor data, and multimedia streams are just a few examples of vast amounts of data that can be of tremendous value to an enterprise if analyzed. The unstructured and semi-structured information provided by raw data feeds is of little value in and of itself. The data needs to be processed to extract information of real value, which can then be stored and managed in the database. Analytics of this data along with the structured data in the database can provide new insights into the data and lead to substantial business benefits.

### 1.2.1 What is MapReduce?

MapReduce is a parallel programming model for processing data on a distributed system. It can process vast amounts of data in a timely manner and can scale linearly. It is particularly effective as a mechanism for batch processing of unstructured and semi-structured data. MapReduce abstracts lower level operations into computations over a set of keys and values.

A simplified definition of a MapReduce job is the successive alternation of two phases, the map phase and the reduce phase. Each map phase applies a transform function over each record in the input data to produce a set of records expressed as key-value pairs. The output from the map phase is input to the reduce phase. In the reduce phase, the map output records are sorted into key-value sets so that all records in a set have the same key value. A reducer function is applied to all the records in a set and a set of output records are produced as key-value pairs. The map phase is logically run in parallel over each record while the reduce phase is run in parallel over all key values.

Note:

Oracle Big Data Connectors do not support the Yet Another Resource Negotiator (YARN) implementation of MapReduce.

### 1.2.2 What is Apache Hadoop?

Apache Hadoop is the software framework for the development and deployment of data processing jobs based on the MapReduce programming model. At the core, Hadoop provides a reliable shared storage and analysis systemFoot 1 . Analysis is provided by MapReduce. Storage is provided by the Hadoop Distributed File System (HDFS), a shared storage system designed for MapReduce jobs.

The Hadoop ecosystem includes several other projects including Apache Avro, a data serialization system that is used by Oracle Loader for Hadoop.

Cloudera's Distribution including Apache Hadoop (CDH) is installed on Oracle Big Data Appliance. You can use Oracle Big Data Connectors on a Hadoop cluster running CDH or the equivalent Apache Hadoop components, as described in the setup instructions in this chapter.

See Also:

- For conceptual information about the Hadoop technologies, the following third-party publication:

  Hadoop: The Definitive Guide, Third Edition by Tom White (O'Reilly Media Inc., 2012, ISBN: 978-1449311520).

- For information about Cloudera's Distribution including Apache Hadoop (CDH4), the Oracle Cloudera website at

  `http://oracle.cloudera.com/`

- For information about Apache Hadoop, the website at

  `http://hadoop.apache.org/`

## 1.3 Downloading the Oracle Big Data Connectors Software

You can download Oracle Big Data Connectors from Oracle Technology Network or Oracle Software Delivery Cloud.

To download from Oracle Technology Network:

1. Use any browser to visit this website:

   `http://www.oracle.com/technetwork/bdc/big-data-connectors/downloads/index.html`

2. Click the name of each connector to download a zip file containing the installation files.

To download from Oracle Software Delivery Cloud:

1. Use any browser to visit this website:

   `https://edelivery.oracle.com/`

2. Accept the Terms and Restrictions to see the Media Pack Search page.

3. Select the search terms:

   Select a Product Pack: Oracle Database

   Platform: Linux x86-64

4. Click Go to display a list of product packs.

5. Select Oracle Big Data Connectors Media Pack for Linux x86-64 (B65965-0x), and then click Continue.

6. Click Download for each connector to download a zip file containing the installation files.

## 1.4 Oracle SQL Connector for Hadoop Distributed File System Setup

You install and configure Oracle SQL Connector for Hadoop Distributed File System (HDFS) on the system where Oracle Database runs. If Hive tables are used as the data source, then you must also install and run Oracle SQL Connector for HDFS on the Hadoop cluster where Hive is installed.

Oracle SQL Connector for HDFS is installed already on Oracle Big Data Appliance if it was configured for Oracle Big Data Connectors.

This section contains the following topics:

- Software Requirements

- Installing and Configuring a Hadoop Client

- Installing Oracle SQL Connector for HDFS

- Providing Support for Hive Tables

- Granting User Privileges in Oracle Database

- Setting Up User Accounts on the Oracle Database System

- Setting Up User Accounts on the Hadoop Cluster

### 1.4.1 Software Requirements

Oracle SQL Connector for HDFS requires the following software:

On the Hadoop cluster:

- Cloudera's Distribution including Apache Hadoop version 3 (CDH3) or version 4 (CDH4), or Apache Hadoop 1.0 (formerly 0.20.2).

- Java Development Kit (JDK) 1.6_08 or later. Consult the distributor of your Hadoop software (Cloudera or Apache) for the recommended version.

- Hive 0.7.0, 0.7.1, 0.8.1, 0.9.0, or 0.10 (required for Hive table access, otherwise optional)

These components are already installed on Oracle Big Data Appliance.

On the Oracle Database system:

- Oracle Database 12c or Oracle Database 11g release 2 (11.2.0.2 or 11.2.0.3) for Linux.

- To support the Oracle Data Pump file format in Oracle Database release 11.2.0.2, an Oracle Database one-off patch. To download this patch, go to `http://support.oracle.com` and search for bug 14557588.

  Release 11.2.0.3 and later releases do not require this patch.

- The same version of Hadoop as your Hadoop cluster, either CDH3, CDH4, or Apache Hadoop 1.0.

- The same version of JDK as your Hadoop cluster.

### 1.4.2 Installing and Configuring a Hadoop Client

Oracle SQL Connector for HDFS works as a Hadoop client. You must install Hadoop on the Oracle Database system and minimally configure it for Hadoop client use only.

However, you do not need to perform a full configuration of Hadoop on the Oracle Database system to run MapReduce jobs for Oracle SQL Connector for HDFS.

To configure the Oracle Database system as a Hadoop client:

1. Install and configure the same version of CDH or Apache Hadoop on the Oracle Database system as on the Hadoop cluster. If you are using Oracle Big Data Appliance, then complete the procedures for providing remote client access in the Oracle Big Data Appliance Software User's Guide. Otherwise, follow the installation instructions provided by the distributor (Cloudera or Apache).

   Note:

   Do not start Hadoop on the Oracle Database system. If it is running, then Oracle SQL Connector for HDFS attempts to use it instead of the Hadoop cluster. Oracle SQL Connector for HDFS just uses the Hadoop JAR files and the configuration files from the Hadoop cluster on the Oracle Database system.

2. Ensure that Oracle Database has access to HDFS:

   1. Log in to the system where Oracle Database is running by using the Oracle Database account.

   2. Open a Bash shell and enter this command:

          hadoop fs -ls /user

      You might need to add the directory containing the Hadoop executable file to the `PATH` environment variable. The default path for CDH is /usr/bin.

      You should see the same list of directories that you see when you run the `hadoop fs` command directly on the Hadoop cluster. If not, then first ensure that the Hadoop cluster is up and running. If the problem persists, then you must correct the Hadoop client configuration so that Oracle Database has access to the Hadoop cluster file system.

The Oracle Database system is now ready for use as a Hadoop client. No other Hadoop configuration steps are needed.

### 1.4.3 Installing Oracle SQL Connector for HDFS

Follow this procedure to install Oracle SQL Connector for HDFS.

To install Oracle SQL Connector for HDFS on the Oracle Database system:

1. Download the zip file to a directory on the system where Oracle Database runs.

2. Unzip orahdfs-version.zip into a permanent directory:

       $ unzip orahdfs-2.2.0.zip
       Archive:  orahdfs-2.2.0.zip
          creating: orahdfs-2.2.0/
          creating: orahdfs-2.2.0/bin/
         inflating: orahdfs-2.2.0/bin/hdfs_stream
          creating: orahdfs-2.2.0/jlib/
         inflating: orahdfs-2.2.0/jlib/orahdfs.jar
         inflating: orahdfs-2.2.0/jlib/ora-hadoop-common.jar
         inflating: orahdfs-2.2.0/jlib/osdt_core.jar
         inflating: orahdfs-2.2.0/jlib/osdt_cert.jar
         inflating: orahdfs-2.2.0/jlib/oraclepki.jar
         inflating: orahdfs-2.2.0/jlib/ojdbc6.jar
          creating: orahdfs-2.2.0/log/
          creating: orahdfs-2.2.0/doc/
         inflating: orahdfs-2.2.0/doc/README.txt

   The unzipped files have the structure shown in Example 1-1.

3. Open the orahdfs-2.2.0/bin/hdfs_stream Bash shell script in a text editor, and make the changes indicated by the comments in the script.

   The hdfs_stream script does not inherit any environment variable settings, and so they are set in the script if they are needed by Oracle SQL Connector for HDFS:

   - `PATH`: If the `hadoop` script is not in /usr/bin:bin (the path initially set in hdfs_stream), then add the Hadoop bin directory, such as /usr/lib/hadoop/bin.

   - `JAVA_HOME`: If Hadoop does not detect Java, then set this variable to the Java installation directory. For example, /usr/bin/java.

   - `OSCH_HOME`: If you moved the script from the orahdfs-version/bin subdirectory, then set this variable to the full path of the orahdfs-2.2.0 directory, which was created in Step 2. Otherwise, Oracle SQL Connector for HDFS detects its location automatically.

   See the comments in the script for more information about these environment variables.

   The hdfs_stream script is the preprocessor for the Oracle Database external table created by Oracle SQL Connector for HDFS.

4. Run hdfs_stream from the Oracle SQL Connector for HDFS installation directory. You should see this usage information:

       $ ./hdfs_stream
       Usage: hdfs_stream locationFile

   If you do not see the usage statement, then ensure that the operating system user that Oracle Database is running under has the following permissions:

   - Read and execute permissions on the hdfs_stream script:

         $ ls -l OSCH_HOME/bin/hdfs_stream
         -rwxr-xr-x 1 oracle oinstall Nov 27 15:51 hdfs_stream

   - Read permission on orahdfs.jar.

         $ ls -l OSCH_HOME/jlib/orahdfs.jar
         -rwxr-xr-x 1 oracle oinstall Nov 27 15:51 orahdfs.jar

   If you do not see these permissions, then enter a `chmod` command to fix them, for example:

       $ chmod 755 OSCH_HOME/bin/hdfs_stream

   In the previous commands, `OSCH_HOME` represents the Oracle SQL Connector for HDFS home directory.

5. Log in to Oracle Database and create a database directory for the orahdfs-version/bin directory where hdfs_stream resides. In this example, Oracle SQL Connector for HDFS is installed in /etc:

       SQL> CREATE OR REPLACE DIRECTORY osch_bin_path AS '/etc/orahdfs-2.2.0/bin';

6. If you are using Oracle Wallet in Oracle Database 12c, then copy these libraries from `ORACLE_HOME`/jlib to `OSCH_HOME`/jlib:

       oraclepki.jar
       osdt_cert.jar
       sdt_core.jar

7. If you plan to access only data stored in HDFS and Data Pump format files, then you are done. If you also plan to access Hive tables, then you must also install software on the Hadoop cluster, as described in "Providing Support for Hive Tables."

The unzipped files have the structure shown in Example 1-1.

Example 1-1 Structure of the orahdfs Directory

    orahdfs-version
       bin/
          hdfs_stream
       doc/
          README.txt
       jlib/
          ojdbc6.jar
          ora-hadoop-common.jar
          oraclepki.jar
          orahdfs.jar
          osdt_cert.jar
          osdt_core.jar
       log/

Figure 1-1 illustrates shows the flow of data and the components locations.

Figure 1-1 Oracle SQL Connector for HDFS Installation for HDFS and Data Pump Files

Description of "Figure 1-1 Oracle SQL Connector for HDFS Installation for HDFS and Data Pump Files"

### 1.4.4 Providing Support for Hive Tables

Complete the following procedure on the Hadoop cluster to support access to Hive tables. If you only plan to access HDFS and Data Pump format files, then you can omit this procedure.

Oracle SQL Connector for HDFS should already be installed on Oracle Big Data Appliance. To verify the installation, ensure that /opt/oracle/orahdfs-2.2.0 exists.

To support Hive tables using a third-party Hadoop cluster:

1. Download or copy the orahdfs-version.zip file to a directory on a node in the Hadoop cluster where Hive is installed.

2. Unzip orahdfs-version.zip into a directory.

3. If you are using Oracle Wallet in Oracle Database 12c, then copy these libraries from `ORACLE_HOME`/jlib on the database system to `OSCH_HOME`/jlib on the Hadoop cluster:

       oraclepki.jar
       osdt_cert.jar
       sdt_core.jar

4. Repeat these steps for all nodes in the cluster.

5. Add the Hive JAR files and the Hive conf directory to the `HADOOP_CLASSPATH` environment variable. To avoid JAR conflicts among the various Hadoop products, Oracle recommends that you set `HADOOP_CLASSPATH` in the local shell initialization script of Oracle SQL Connector for HDFS users instead of making a global change to `HADOOP_CLASSPATH`. See "Setting Up User Accounts on the Hadoop Cluster."

Figure 1-2 illustrates the flow of data and the component locations

Figure 1-2 Oracle SQL Connector for HDFS Installation for Hive Tables

Description of "Figure 1-2 Oracle SQL Connector for HDFS Installation for Hive Tables"

### 1.4.5 Granting User Privileges in Oracle Database

Oracle Database users require these privileges when using Oracle SQL Connector for HDFS to create external tables:

- `CREATE SESSION`

- `CREATE TABLE`

- `EXECUTE` on the `UTL_FILE` PL/SQL package

- `READ` and `EXECUTE` on the `OSCH_BIN_PATH` directory created during the installation of Oracle SQL Connector for HDFS. Do not grant write access to anyone. Grant `EXECUTE` only to those who intend to use Oracle SQL Connector for HDFS.

- `READ` and `WRITE` on a database directory for storing external tables, or the `CREATE ANY DIRECTORY` system privilege.

- A tablespace and quota for copying data into the Oracle database. Optional.

Example 1-2 shows the SQL commands granting these privileges to `HDFSUSER`.

Example 1-2 Granting Users Access to Oracle SQL Connector for HDFS

    CONNECT / AS sysdba;
    CREATE USER hdfsuser IDENTIFIED BY password
         DEFAULT TABLESPACE hdfsdata
         QUOTA UNLIMITED ON hdfsdata;
    GRANT CREATE SESSION, CREATE TABLE TO hdfsuser;
    GRANT EXECUTE ON sys.utl_file TO hdfsuser;
    GRANT READ, EXECUTE ON DIRECTORY osch_bin_path TO hdfsuser;
    GRANT READ, WRITE ON DIRECTORY external_table_dir TO hdfsuser;

Note:

To query an external table that uses Oracle SQL Connector for HDFS, users only need the `SELECT` privilege on the table.

### 1.4.6 Setting Up User Accounts on the Oracle Database System

To create external tables for HDFS and Data Pump format files, users can log in to either the Oracle Database system or a node in the Hadoop cluster. For Hive access, user must log in to the cluster.

You can set up an account on the Oracle Database system the same as you would for any other operating system user. `HADOOP_CLASSPATH` must include path/orahdfs-2.2.0/jlib/*. You can add this setting to the shell profile as part of this installation procedure, or users can set it themselves. The following example alters `HADOOP_CLASSPATH` in the Bash shell where Oracle SQL Connector for HDFS is installed in /usr/bin:

    export HADOOP_CLASSPATH="$HADOOP_CLASSPATH:/usr/bin/orahdfs-2.2.0/jlib/*

### 1.4.7 Setting Up User Accounts on the Hadoop Cluster

For Hive access, users must have a home directory and be able to log in to the nodes of a Hadoop cluster. After logging in to a node, users can run Oracle SQL Connector for HDFS to create Oracle Database external tables for all supported data sources.

To set up a Hadoop user account for Oracle SQL Connector for HDFS:

1. Create home directories in HDFS and in the local file system.

   For Oracle Big Data Appliance, see the instructions for creating new HDFS users in the Oracle Big Data Appliance Software User's Guide.

   For a Hadoop cluster running on commodity hardware, you can follow the same basic steps as you would on Oracle Big Data Appliance. The only difference is that you cannot use `dcli` to replicate your changes across all nodes.

2. Modify the shell configuration file (such as .bashrc for the Bash shell), to add the necessary JAR files to `HADOOP_CLASSPATH`:

       path/orahdfs-2.2.0/jlib/*
       /usr/lib/hive/lib/*
       /etc/hive/conf

   The following Bash command alters `HADOOP_CLASSPATH` on Oracle Big Data Appliance:

       export HADOOP_CLASSPATH="$HADOOP_CLASSPATH:/opt/oracle/orahdfs-2.2.0/jlib/*:/usr/lib/hive/lib/*:/etc/hive/conf"

3. Replicate the altered file across all nodes of the cluster. This command replicates the Bash shell configuration file across all nodes in Oracle Big Data Appliance:

       # dcli cp -f /home/user_name/.bashrc -d /home/user_name

See Also:

Oracle Big Data Appliance Owner's Guide for the full syntax of the `dcli` command.

## 1.5 Oracle Loader for Hadoop Setup

Before installing Oracle Loader for Hadoop, verify that you have the required software.

### 1.5.1 Software Requirements

Oracle Loader for Hadoop requires the following software:

- A target database system running one of the following:

  - Oracle Database 11g release 2 (11.2.0.2) with required patch

  - Oracle Database 11g release 2 (11.2.0.3)

  - Oracle Database 12c

  Note:

  To use Oracle Loader for Hadoop with Oracle Database 11g release 2 (11.2.0.2), you must first apply a one-off patch that addresses bug number 11897896. To access this patch, go to `http://support.oracle.com` and search for the bug number.

- Cloudera's Distribution including Apache Hadoop version 3 (CDH3) or version 4 (CDH4), or Apache Hadoop 1.0 (formerly 0.20.2).

- Hive 0.7.0, 0.8.1, 0.9.0, or 0.10.0 if you are loading data from Hive tables.

### 1.5.2 Installing Oracle Loader for Hadoop

Oracle Loader for Hadoop is packaged with the Oracle Database 11g release 2 client libraries and Oracle Instant Client libraries for connecting to Oracle Database 11.2.0.2 or 11.2.0.3.

To install Oracle Loader for Hadoop:

1. Unpack the content of `oraloader-``version``.x86_64.zip` into a directory on your Hadoop cluster. This archive contains two archives:

   - oraloader-version-h1.x86_64.zip: Use with CDH3 and Apache Hadoop 1.0

   - oraloader-version-h2.x86_64.zip: Use with CDH4

2. Unzip the appropriate archive into a directory on your Hadoop cluster.

   A directory named oraloader-version-hn is created with the following subdirectories:

       doc
       jlib
       lib
       examples

3. Create a variable named `OLH_HOME` and set it to the installation directory.

4. Add `$OLH_HOME/jlib/*` to the `HADOOP_CLASSPATH` variable.

5. Add `$KVHOME/lib/kvstore.jar` to the `HADOOP_CLASSPATH` variable, if you are reading data from Oracle NoSQL Database Release 2.

6. If you are using Oracle Wallet in Oracle Database 12c, then copy these libraries from `ORACLE_HOME`/jlib on the database system to `OLH_HOME` on the Hadoop cluster:

       oraclepki.jar
       osdt_cert.jar
       sdt_core.jar

### 1.5.3 Providing Support for Offline Database Mode

In a typical installation, Oracle Loader for Hadoop can connect to the Oracle Database system from the Hadoop cluster where the loader is installed. If this connection is impossible—for example, the two systems are located on distinct networks—then you can use Oracle Loader for Hadoop in offline database mode. You must install Oracle Loader for Hadoop on both the database system and on the Hadoop cluster. See "About the Modes of Operation."

To support Oracle Loader for Hadoop in offline database mode:

1. Unpack the content of `oraloader-``version``.zip` into a directory on the Oracle Database system.

2. Unzip the same version of the software as you installed on the Hadoop cluster, either for CDH3 or CDH4.

3. Create a variable named `OLH_HOME` and set it to the installation directory. This example uses the Bash shell syntax:

       $ export OLH_HOME="/usr/bin/oraloader-2.2.0-h2/"

4. Add the Oracle Loader for Hadoop JAR files to the `CLASSPATH` environment variable. This example uses the Bash shell syntax:

       $ export CLASSPATH=$CLASSPATH:$OLH_HOME/jlib/*

## 1.6 Oracle Data Integrator Application Adapter for Hadoop Setup

Installation requirements for Oracle Data Integrator (ODI) Application Adapter for Hadoop are provided in these topics:

- System Requirements and Certifications

- Technology-Specific Requirements

- Location of Oracle Data Integrator Application Adapter for Hadoop

- Setting Up the Topology

### 1.6.1 System Requirements and Certifications

To use Oracle Data Integrator Application Adapter for Hadoop, you must first have Oracle Data Integrator, which is licensed separately from Oracle Big Data Connectors. You can download ODI from the Oracle website at

`http://www.oracle.com/technetwork/middleware/data-integrator/downloads/index.html`

Oracle Data Integrator Application Adapter for Hadoop requires a minimum version of Oracle Data Integrator 11.1.1.6.0.

Before performing any installation, read the system requirements and certification documentation to ensure that your environment meets the minimum installation requirements for the products that you are installing.

The list of supported platforms and versions is available on Oracle Technology Network:

`http://www.oracle.com/technetwork/middleware/data-integrator/overview/index.html`

### 1.6.2 Technology-Specific Requirements

The list of supported technologies and versions is available on Oracle Technical Network:

`http://www.oracle.com/technetwork/middleware/data-integrator/overview/index.html`

### 1.6.3 Location of Oracle Data Integrator Application Adapter for Hadoop

Oracle Data Integrator Application Adapter for Hadoop is available in the xml-reference directory of the Oracle Data Integrator Companion CD.

### 1.6.4 Setting Up the Topology

To set up the topology, see Chapter 4, "Oracle Data Integrator Application Adapter for Hadoop."

## 1.7 Oracle R Connector for Hadoop Setup

Oracle R Connector for Hadoop requires the installation of a software environment on the Hadoop side and on a client Linux system.

### 1.7.1 Installing the Software on Hadoop

Oracle Big Data Appliance supports Oracle R Connector for Hadoop without any additional software installation or configuration. However, you do need to verify whether certain R packages are installed. See "Installing Additional R Packages."

However, to use Oracle R Connector for Hadoop on any other Hadoop cluster, you must create the necessary environment.

#### 1.7.1.1 Software Requirements for a Third-Party Hadoop Cluster

You must install several software components on a third-party Hadoop cluster to support Oracle R Connector for Hadoop.

Install these components on third-party servers:

- Cloudera's Distribution including Apache Hadoop version 4 (CDH4) or Apache Hadoop 2.0.0, using MapReduce 1.

  Complete the instructions provided by the distributor.

- Hive 0.7.1 or 0.9.0

  See "Installing Hive on a Hadoop Cluster."

- Sqoop for the execution of functions that connect to Oracle Database. Oracle R Connector for Hadoop does not require Sqoop to install or load.

  See "Installing Sqoop on a Hadoop Cluster."

- Mahout for the execution of (`orch_lmf_mahout_als.R`).

- Java Virtual Machine (JVM), preferably Java HotSpot Virtual Machine 6.

  Complete the instructions provided at the download site at

  `http://www.oracle.com/technetwork/java/javase/downloads/index.html`

- Oracle R Distribution 2.15.1 with all base libraries on all nodes in the Hadoop cluster.

  See "Installing R on a Hadoop Cluster."

- The ORCH package on each R engine, which must exist on every node of the Hadoop cluster.

  See "Installing the ORCH Package on a Hadoop Cluster".

- Oracle Loader for Hadoop to support the OLH driver (optional). See "Oracle Loader for Hadoop Setup."

Note:

Do not set `HADOOP_HOME` on the Hadoop cluster. CDH4 does not need it, and it interferes with Oracle R Connector for Hadoop when it checks the status of the JobTracker. This results in the error "Something is terribly wrong with Hadoop MapReduce."

If you must set `HADOOP_HOME` for another application, then also set `HADOOP_LIBEXEC_DIR` in the /etc/bashrc file. For example:

    export HADOOP_LIBEXEC_DIR=/usr/lib/hadoop/libexec

#### 1.7.1.2 Installing Sqoop on a Hadoop Cluster

Sqoop provides a SQL-like interface to Hadoop, which is a Java-based environment. Oracle R Connector for Hadoop uses Sqoop for access to Oracle Database.

Note:

Sqoop is required even when using Oracle Loader for Hadoop as a driver for loading data into Oracle Database. Sqoop performs additional functions, such as copying data from a database to HDFS and sending free-form queries to a database. The OLH driver also uses Sqoop to perform operations that Oracle Loader for Hadoop does not support.

To install and configure Sqoop for use with Oracle Database:

1. Install Sqoop if it is not already installed on the server.

   For Cloudera's Distribution including Apache Hadoop, see the Sqoop installation instructions in the CDH Installation Guide at

   `http://oracle.cloudera.com/`

2. Download the appropriate Java Database Connectivity (JDBC) driver for Oracle Database from Oracle Technology Network at

   `http://www.oracle.com/technetwork/database/features/jdbc/index-091264.html`

3. Copy the driver JAR file to `$SQOOP_HOME`/lib, which is a directory such as /usr/lib/sqoop/lib.

4. Provide Sqoop with the connection string to Oracle Database.

       $ sqoop import --connect jdbc_connection_string

   For example, `sqoop import --connect jdbc:oracle:thin@myhost:1521/orcl`.

#### 1.7.1.3 Installing Hive on a Hadoop Cluster

Hive provides an alternative storage and retrieval mechanism to HDFS files through a querying language called HiveQL. Oracle R Connector for Hadoop uses the data preparation and analysis features of HiveQL, while enabling you to use R language constructs.

To install Hive:

1. Follow the instructions provided by the distributor (Cloudera or Apache) for installing Hive.

2. Verify that the installation is working correctly:

3.     $ hive -H
       usage: hive
        -d,--define <key=value>          Variable subsitution to apply to hive
                                         commands. e.g. -d A=B or --define A=B
           --database <databasename>     Specify the database to use
        -e <quoted-query-string>         SQL from command line
        -f <filename>                    SQL from files
        -H,--help                        Print help information
        -h <hostname>                    connecting to Hive Server on remote host
           --hiveconf <property=value>   Use value for given property
           --hivevar <key=value>         Variable subsitution to apply to hive
                                         commands. e.g. --hivevar A=B
        -i <filename>                    Initialization SQL file
        -p <port>                        connecting to Hive Server on port number
        -S,--silent                      Silent mode in interactive shell
        -v,--verbose                     Verbose mode (echo executed SQL to the
                                         console)

4. If the command fails or you see warnings in the output, then fix the Hive installation.

#### 1.7.1.4 Installing R on a Hadoop Cluster

You can download Oracle R Distribution 2.15.1 and get the installation instructions from the website at

`http://www.oracle.com/technetwork/indexes/downloads/r-distribution-1532464.html`

Alternatively, you can download R from a Comprehensive R Archive Network (CRAN) website at

`http://www.r-project.org`

#### 1.7.1.5 Installing the ORCH Package on a Hadoop Cluster

ORCH is the name of the Oracle R Connector for Hadoop package.

To install the ORCH package:

1. Set the environment variables for the supporting software:

       $ export JAVA_HOME="/usr/lib/jdk6"
       $ export R_HOME="/usr/lib64/R"
       $ export SQOOP_HOME "/usr/lib/sqoop"

2. Unzip the downloaded file:

       $ unzip orch-version.zip
       Archive:  orch-linux-x86_64-2.1.0.zip
        extracting: ORCH2.1.0/ORCH_2.1.0_R_x86_64-unknown-linux-gnu.tar.gz
         inflating: ORCH2.1.0/ORCHcore_2.1.0_R_x86_64-unknown-linux-gnu.tar.gz
         inflating: ORCH2.1.0/OREbase_1.3.1_R_x86_64-unknown-linux-gnu.tar.gz
         inflating: ORCH2.1.0/OREstats_1.3.1_R_x86_64-unknown-linux-gnu.tar.gz

3. Change to the new directory:

       $ cd ORCH2.1.0

4. Install the packages in the exact order shown here:

       $ R --vanilla CMD INSTALL OREbase_1.3.1_R_x86_64-unknown-linux-gnu.tar.gz
       $ R --vanilla CMD INSTALL OREstats_1.3.1_R_x86_64-unknown-linux-gnu.tar.gz
       $ R --vanilla CMD INSTALL ORCHcore_2.1.0_R_x86_64-unknown-linux-gnu.tar.gz
       $ R --vanilla CMD INSTALL ORCH_2.1.0_R_x86_64-unknown-linux-gnu.tar.gz
       $ R --vanilla CMD INSTALL ORCHstats_2.1.0_R_x86_64-unknown-linux-gnu.tar.gz

### 1.7.2 Installing Additional R Packages

Your Hadoop cluster must have `libpng-devel` installed on every node. If you are using a cluster running on commodity hardware, then you can follow the same basic procedures. However, you cannot use the `dcli` utility to replicate the commands across all nodes. See the Oracle Big Data Appliance Owner's Guide for the syntax of the `dcli` utility.

To install libpng-devel:

1. Log in as `root` to any node in your Hadoop cluster.

2. Check whether `libpng-devel` is already installed:

       # dcli rpm -qi libpng-devel
       bda1node01: package libpng-devel is not installed
       bda1node02: package libpng-devel is not installed
            .
            .
            .

   If the package is already installed on all servers, then you can skip this procedure.

3. If you need a proxy server to go outside a firewall, then set the `HTTP_PROXY` environment variable:

       # dcli export HTTP_PROXY="http://proxy.example.com"

4. Change to the yum directory:

       # cd /etc/yum.repos.d

5. Download and configure the appropriate configuration file for your version of Linux:

   For Enterprise Linux 5 (EL5):

   1. Download the yum configuration file:

          # wget http://public-yum.oracle.com/public-yum-el5.repo

   2. Open public-yum-el5.repo in a text editor and make these changes:

      Under `el5_latest`, set `enabled=1`

      Under `el5_addons`, set `enabled=1`

   3. Save your changes and exit.

   4. Copy the file to the other Oracle Big Data Appliance servers:

          # dcli -d /etc/yum.repos.d -f public-yum-el5.repo

   For Oracle Linux 6 (OL6):

   1. Download the yum configuration file:

          # wget http://public-yum.oracle.com/public-yum-ol6.repo

   2. Open public-yum-ol6.repo in a text editor and make these changes:

      Under `ol6_latest`, set `enabled=1`

      Under `ol6_addons`, set `enabled=1`

   3. Save your changes and exit.

   4. Copy the file to the other Oracle Big Data Appliance servers:

          # dcli -d /etc/yum.repos.d -f public-yum-ol6.repo

6. Install the package on all servers:

       # dcli yum -y install libpng-devel
       bda1node01: Loaded plugins: rhnplugin, security
       bda1node01: Repository 'bda' is missing name in configuration, using id
       bda1node01: This system is not registered with ULN.
       bda1node01: ULN support will be disabled.
       bda1node01: http://bda1node01-master.us.oracle.com/bda/repodata/repomd.xml:
       bda1node01: [Errno 14] HTTP Error 502: notresolvable
       bda1node01: Trying other mirror.
            .
            .
            .
       bda1node01: Running Transaction
       bda1node01: Installing     : libpng-devel                                 1/2
       bda1node01: Installing     : libpng-devel                                 2/2

       bda1node01: Installed:
       bda1node01: libpng-devel.i386 2:1.2.10-17.el5_8  ibpng-devel.x86_64 2:1.2.10-17.el5_8

       bda1node01: Complete!
       bda1node02: Loaded plugins: rhnplugin, security
            .
            .
            .

7. Verify that the installation was successful on all servers:

       # dcli rpm -qi libpng-devel
       bda1node01: Name        : libpng-devel                      Relocations: (not relocatable)
       bda1node01: Version     : 1.2.10                                 Vendor: Oracle America
       bda1node01: Release     : 17.el5_8                           Build Date: Wed 25 Apr 2012 06:51:15 AM PDT
       bda1node01: Install Date: Tue 05 Feb 2013 11:41:14 AM PST    Build Host: ca-build56.us.oracle.com
       bda1node01: Group       : Development/Libraries              Source RPM: libpng-1.2.10-17.el5_8.src.rpm
       bda1node01: Size        : 482483                                License: zlib
       bda1node01: Signature   : DSA/SHA1, Wed 25 Apr 2012 06:51:41 AM PDT, Key ID 66ced3de1e5e0159
       bda1node01: URL         : http://www.libpng.org/pub/png/
       bda1node01: Summary     : Development tools for programs to manipulate PNG image format files.
       bda1node01: Description :
       bda1node01: The libpng-devel package contains the header files and static
       bda1node01: libraries necessary for developing programs using the PNG (Portable
       bda1node01: Network Graphics) library.
            .
            .
            .

### 1.7.3 Providing Remote Client Access to R Users

Whereas R users will run their programs as MapReduce jobs on the Hadoop cluster, they do not typically have individual accounts on that platform. Instead, an external Linux server provides remote access.

#### 1.7.3.1 Software Requirements for Remote Client Access

To provide access to a Hadoop cluster to R users, install these components on a Linux server:

- The same version of Hadoop as your Hadoop cluster; otherwise, unexpected issues and failures can occur

- The same version of Sqoop as your Hadoop cluster; required only to support copying data in and out of Oracle databases

- Mahout; required only for the `orch.ls` function with the Mahout ALS-WS algorithm

- The same version of the Java Development Kit (JDK) as your Hadoop cluster

- R distribution 2.15.1 with all base libraries

- ORCH R package

To provide access to database objects, you must have the Oracle Advanced Analytics option to Oracle Database. Then you can install this additional component on the Hadoop client:

- Oracle R Enterprise Client Packages

#### 1.7.3.2 Configuring the Server as a Hadoop Client

You must install Hadoop on the client and minimally configure it for HDFS client use.

To install and configure Hadoop on the client system:

1. Install and configure CDH3 or Apache Hadoop 0.20.2 on the client system. This system can be the host for Oracle Database. If you are using Oracle Big Data Appliance, then complete the procedures for providing remote client access in the Oracle Big Data Appliance Software User's Guide. Otherwise, follow the installation instructions provided by the distributor (Cloudera or Apache).

2. Log in to the client system as an R user.

3. Open a Bash shell and enter this Hadoop file system command:

       $HADOOP_HOME/bin/hadoop fs -ls /user

4. If you see a list of files, then you are done. If not, then ensure that the Hadoop cluster is up and running. If that does not fix the problem, then you must debug your client Hadoop installation.

#### 1.7.3.3 Installing Sqoop on a Hadoop Client

Complete the same procedures on the client system for installing and configuring Sqoop as those provided in "Installing Sqoop on a Hadoop Cluster".

#### 1.7.3.4 Installing R on a Hadoop Client

You can download R 2.13.2 and get the installation instructions from the Oracle R Distribution website at

`http://oss.oracle.com/ORD/`

When you are done, ensure that users have the necessary permissions to connect to the Linux server and run R.

You may also want to install RStudio Server to facilitate access by R users. See the RStudio website at

`http://rstudio.org/`

#### 1.7.3.5 Installing the ORCH Package on a Hadoop Client

Complete the procedures on the client system for installing `ORCH` as described in "Installing the Software on Hadoop".

#### 1.7.3.6 Installing the Oracle R Enterprise Client Packages (Optional)

To support full access to Oracle Database using R, install the Oracle R Enterprise Release 1.3.1 or later client packages. Without them, Oracle R Connector for Hadoop does not have access to the advanced statistical algorithms provided by Oracle R Enterprise.

See Also:

Oracle R Enterprise User's Guide for information about installing R and Oracle R Enterprise

Footnote Legend

Footnote 1: Hadoop: The Definitive Guide, Third Edition by Tom White (O'Reilly Media Inc., 2012, 978-1449311520).