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h2o.import_sql_table

Import SQL Table into H2O


Description

Imports SQL table into an H2O cluster. Assumes that the SQL table is not being updated and is stable. Runs multiple SELECT SQL queries concurrently for parallel ingestion. 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' Also see h2o.import_sql_select. Currently supported SQL databases are MySQL, PostgreSQL, MariaDB, Hive, Oracle and Microsoft SQL Server.

Usage

h2o.import_sql_table(
  connection_url,
  table,
  username,
  password,
  columns = NULL,
  optimize = NULL,
  fetch_mode = NULL
)

Arguments

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"

table

Name of SQL table

username

Username for SQL server

password

Password for SQL server

columns

(Optional) Character vector of column names to import from SQL table. Default is to import all columns.

optimize

(Optional) Optimize import of SQL table for faster imports. Default is true. Ignored - use fetch_mode instead.

fetch_mode

(Optional) Set to DISTRIBUTED to enable distributed import. Set to SINGLE to force a sequential read from the database Can be used for databases that do not support OFFSET-like clauses in SQL statements.

Details

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


h2o

R Interface for the 'H2O' Scalable Machine Learning Platform

v3.32.1.2
Apache License (== 2.0)
Authors
Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], Tomas Fryda [ctb], H2O.ai [cph, fnd]
Initial release
2021-04-29

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