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:
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)