Uploading a File

Unlike the import function, which is a parallelized reader, the upload function is a push from the client to the server. The specified path must be a client-side path. This is not scalable and is only intended for smaller data sizes. The client pushes the data from a local filesystem (for example, on your machine where R or Python is running) to H2O. For big-data operations, you don’t want the data stored on or flowing through the client.

Refer to the Supported File Formats topic to ensure that you are using a supported file type.

Note: When parsing a data file containing timestamps that do not include a timezone, the timestamps will be interpreted as UTC (GMT). You can override the parsing timezone using the following:

  • R: h2o.setTimezone("America/Los Angeles")

  • Python: h2o.cluster().timezone = "America/Los Angeles"

Run the following command to load data that resides on the same machine that is running H2O.

R

Python

library(h2o)
h2o.init()
iris_path <- "../smalldata/iris/iris_wheader.csv"
iris <- h2o.uploadFile(path = iris_path)

import h2o
h2o.init()
iris_df = h2o.upload_file("../smalldata/iris/iris_wheader.csv")