Getting Data into H2O¶

Alluxio FS¶

Required Library

To access Alluxio data source, an Alluxio client library that is part of Alluxio distribution is required. For example, alluxio-1.3.0/core/client/target/alluxio-core-client-1.3.0-jar-with-dependencies.jar.

H2O Command Line

java -cp alluxio-core-client-1.3.0-jar-with-dependencies.jar:build/h2o.jar water.H2OApp

URI Scheme

An Alluxio data source is referenced using alluxio:// schema and location of Alluxio master. For example,

alluxio://localhost:19998/iris.csv

core-site.xml Configuration

Not supported.

IBM Swift Object Storage¶

Required Library

To access IBM Object Store (which can be exposed via Bluemix or Softlayer), IBM’s HDFS driver hadoop-openstack.jar is required. The driver can be obtained, for example, by running BigInsight instances at location /usr/iop/4.2.0.0/hadoop-mapreduce/hadoop-openstack.jar.

Note: The jar available at Maven central is not compatible with IBM Swift Object Storage.

H2O Command Line

java -cp hadoop-openstack.jar:h2o.jar water.H2OApp

URI Scheme

Data source is available under the regular Swift URI structure: swift://<CONTAINER>.<SERVICE>/path/to/file For example,

swift://smalldata.h2o/iris.csv

core-site.xml Configuration

The core-site.xml needs to be configured with Swift Object Store parameters. These are available in the Bluemix/Softlayer management console.

<configuration>
  <property>
    <name>fs.swift.service.SERVICE.auth.url</name>
    <value>https://identity.open.softlayer.com/v3/auth/tokens</value>
  </property>
  <property>
    <name>fs.swift.service.SERVICE.project.id</name>
    <value>...</value>
  </property>
  <property>
    <name>fs.swift.service.SERVICE.user.id</name>
    <value>...</value>
  </property>
  <property>
    <name>fs.swift.service.SERVICE.password</name>
    <value>...</value>
  </property>
  <property>
    <name>fs.swift.service.SERVICE.region</name>
    <value>dallas</value>
  </property>
  <property>
    <name>fs.swift.service.SERVICE.public</name>
    <value>false</value>
  </property>
</configuration>

Google Cloud Storage Connector for Hadoop & Spark¶

Required Library

To access the Google Cloud Store Object Store, Google’s cloud storage connector, gcs-connector-latest-hadoop2.jar is required. The official documentation and driver can be found here.

H2O Command Line

H2O on Hadoop:
hadoop jar h2o-driver.jar -libjars /path/to/gcs-connector-latest-hadoop2.jar

Sparkling Water
export SPARK_CLASSPATH=/home/nick/spark-2.0.2-bin-hadoop2.6/lib_managed/jar/gcs-connector-latest-hadoop2.jar
sparkling-water-2.0.5/bin/sparkling-shell --conf "spark.executor.memory=10g"

URI Scheme

Data source is available under the regular Google Storage URI structure: gs://<BUCKETNAME>/path/to/file For example,

gs://mybucket/iris.csv

core-site.xml Configuration

core-site.xml must be configured for at least the following properties (class, project-id, bucketname) as shown in the example below. A full list of configuration options is found here.

<configuration>
    <property>
            <name>fs.gs.impl</name>
            <value>com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem</value>
    </property>
    <property>
            <name>fs.gs.project.id</name>
            <value>my-google-project-id</value>
    </property>
    <property>
            <name>fs.gs.system.bucket</name>
            <value>mybucket</value>
    </property>
</configuration>

import_sql_table¶

This function imports a SQL table to H2OFrame in memory. This function assumes that the SQL table is not being updated and is stable. Users can run multiple SELECT SQL queries concurrently for parallel ingestion.

Note: Be sure to start the h2o.jar in the terminal with your downloaded JDBC driver in the classpath:

java -cp <path_to_h2o_jar>:<path_to_jdbc_driver_jar> water.H2OApp

The import_sql_table function accepts the following parameters:

• connection_url: The URL of the SQL database connection as specified by the Java Database Connectivity (JDBC) Driver. For example, “jdbc:mysql://localhost:3306/menagerie?&useSSL=false“
• table: The name of the SQL table
• columns: A list of column names to import from SQL table. Default is to import all columns.
• username: The username for SQL server
• password: The password for SQL server
• optimize: Specifies to optimize the import of SQL table for faster imports. Note that this option is experimental.

connection_url <- "jdbc:mysql://172.16.2.178:3306/ingestSQL?&useSSL=false"
table <- "citibike20k"
username <- "root"
password <- "abc123"
my_citibike_data <- h2o.import_sql_table(connection_url, table, username, password)

connection_url = "jdbc:mysql://172.16.2.178:3306/ingestSQL?&useSSL=false"
table = "citibike20k"
username = "root"
password = "abc123"
my_citibike_data = h2o.import_sql_table(connection_url, table, username, password)

import_sql_select¶

This function imports the SQL table that is the result of the specified SQL query to H2OFrame in memory. It creates a temporary SQL table from the specified sql_query. Users can run multiple SELECT SQL queries on the temporary table concurrently for parallel ingestion, and then drop the table.

Note: Be sure to start the h2o.jar in the terminal with your downloaded JDBC driver in the classpath:

java -cp <path_to_h2o_jar>:<path_to_jdbc_driver_jar> water.H2OApp

The import_sql_select function accepts the following parameters:

• connection_url: URL of the SQL database connection as specified by the Java Database Connectivity (JDBC) Driver. For example, “jdbc:mysql://localhost:3306/menagerie?&useSSL=false“
• select_query: SQL query starting with SELECT that returns rows from one or more database tables.
• username: The username for the SQL server
• password: The password for the SQL server
• optimize: Specifies to optimize import of SQL table for faster imports. Note that this option is experimental.

connection_url <- "jdbc:mysql://172.16.2.178:3306/ingestSQL?&useSSL=false"
select_query <-  "SELECT  bikeid  from  citibike20k"
username <- "root"
password <- "abc123"
my_citibike_data <- h2o.import_sql_select(connection_url, select_query, username, password)

connection_url = "jdbc:mysql://172.16.2.178:3306/ingestSQL?&useSSL=false"
select_query = "SELECT bikeid from citibike20k"
username = "root"
password = "abc123"
my_citibike_data = h2o.import_sql_select(connection_url, select_query, username, password)