extensionprocessnode properties

Extension Transform node icon With the Extension Transform node, you can take data from a flow and apply transformations to the data using R scripting or Python for Spark scripting.

Python for Spark example

import modeler.api
stream = modeler.script.stream()
node = stream.create("extension_process", "extension_process")
node.setPropertyValue("syntax_type", "Python")

process_script = """
import spss.pyspark.runtime
from pyspark.sql.types import *

cxt = spss.pyspark.runtime.getContext()

if cxt.isComputeDataModelOnly():
    _schema = StructType([StructField("Age", LongType(), nullable=True), \
                      StructField("Sex", StringType(), nullable=True), \
                      StructField("BP", StringType(), nullable=True), \
                      StructField("Na", DoubleType(), nullable=True), \
                      StructField("K", DoubleType(), nullable=True), \
                      StructField("Drug", StringType(), nullable=True)])
    cxt.setSparkOutputSchema(_schema)
else:
    df = cxt.getSparkInputData()
    print df.dtypes[:]
    _newDF = df.select("Age","Sex","BP","Na","K","Drug")
    print _newDF.dtypes[:]
    cxt.setSparkOutputData(_newDF)
"""

node.setPropertyValue("python_syntax", process_script)

R example

node.setPropertyValue("syntax_type", "R")
node.setPropertyValue("r_syntax", """day<-as.Date(modelerData$dob, format="%Y-%m-%d")
next_day<-day + 1
modelerData<-cbind(modelerData,next_day)
var1<-c(fieldName="Next day",fieldLabel="",fieldStorage="date",fieldMeasure="",fieldFormat="",
fieldRole="")
modelerDataModel<-data.frame(modelerDataModel,var1)""")

Table 1. extensionprocessnode properties
`extensionprocessnode` properties	Data type	Property description
`syntax_type`	R Python	Specify which script runs – R or Python (R is the default).
`r_syntax`	string	The R scripting syntax to run.
`python_syntax`	string	The Python scripting syntax to run.
`use_batch_size`	flag	Enable use of batch processing.
`batch_size`	integer	Specify the number of data records to include in each batch.
`convert_flags`	`StringsAndDoubles LogicalValues`	Option to convert flag fields.
`convert_missing`	flag	Option to convert missing values to the R `NA` value.
`convert_datetime`	flag	Option to convert variables with date or datetime formats to R date/time formats.
`convert_datetime_class`	`POSIXct POSIXlt`	Options to specify to what format variables with date or datetime formats are converted.