Importing a File

Unlike the upload function, which is a push from the client to the server, the import function is a parallelized reader and pulls information from the server from a location specified by the client. The path is a server-side path. This is a fast, scalable, highly optimized way to read data. H2O pulls the data from a data store and initiates the data transfer as a read operation.

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"

# To import small iris data file from H2O’s package:
> library(h2o)
> h2o.init()
> irisPath <- "https://s3.amazonaws.com/h2o-airlines-unpacked/allyears2k.csv"
> iris.hex <- h2o.importFile(path = irisPath, destination_frame = "iris.hex")

# To import from HDFS:
> library(h2o)
> h2o.init()
> airlinesURL <- "https://s3.amazonaws.com/h2o-airlines-unpacked/allyears2k.csv"
> airlines.hex <- h2o.importFile(path = airlinesURL, destination_frame = "airlines.hex")

# Import a file from HDFS:
>>> import h2o
>>> h2o.init()
>>> prostate = "https://raw.github.com/h2oai/h2o/master/smalldata/logreg/prostate.csv"
>>> prostate_df = h2o.import_file(path=prostate)