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. .. example-code:: .. code-block:: r > library(h2o) > h2o.init() > irisPath <- "../smalldata/iris/iris_wheader.csv" > iris.hex <- h2o.uploadFile(path = irisPath, destination_frame = "iris.hex") .. code-block:: python >>> import h2o >>> h2o.init() >>> iris_df = h2o.upload_file("../smalldata/iris/iris_wheader.csv")