Transforms

Data wrangling and mapping from one schema to another.
Data wrangling
One of the key tools in DataVec is transformations. DataVec helps the user map a dataset from one schema to another, and provides a list of operations to convert types, format data, and convert a 2D dataset to sequence data.
Building a transform process
A transform process requires a Schema to successfully transform data. Both schema and transform process classes come with a helper Builder class which are useful for organizing code and avoiding complex constructors.
When both are combined together they look like the sample code below. Note how inputDataSchema is passed into the Builder constructor. Your transform process will fail to compile without it.
import org.datavec.api.transform.TransformProcess;
​
TransformProcess tp = new TransformProcess.Builder(inputDataSchema)
    .removeColumns("CustomerID","MerchantID")
    .filter(new ConditionFilter(new CategoricalColumnCondition("MerchantCountryCode", ConditionOp.NotInSet, new HashSet<>(Arrays.asList("USA","CAN")))))
    .conditionalReplaceValueTransform(
        "TransactionAmountUSD",     //Column to operate on
        new DoubleWritable(0.0),    //New value to use, when the condition is satisfied
        new DoubleColumnCondition("TransactionAmountUSD",ConditionOp.LessThan, 0.0)) //Condition: amount < 0.0
    .stringToTimeTransform("DateTimeString","YYYY-MM-DD HH:mm:ss.SSS", DateTimeZone.UTC)
    .renameColumn("DateTimeString", "DateTime")
    .transform(new DeriveColumnsFromTimeTransform.Builder("DateTime").addIntegerDerivedColumn("HourOfDay", DateTimeFieldType.hourOfDay()).build())
    .removeColumns("DateTime")
    .build();
Executing a transformation
Different "backends" for executors are available. Using the tp transform process above, here's how you can execute it locally using plain DataVec.
import org.datavec.local.transforms.LocalTransformExecutor;
​
List<List<Writable>> processedData = LocalTransformExecutor.execute(originalData, tp);
Debugging
Each operation in a transform process represents a "step" in schema changes. Sometimes, the resulting transformation is not the intended result. You can debug this by printing each step in the transform tp with the following:
//Now, print the schema after each time step:
int numActions = tp.getActionList().size();
​
for(int i=0; i<numActions; i++ ){
    System.out.println("\n\n==================================================");
    System.out.println("-- Schema after step " + i + " (" + tp.getActionList().get(i) + ") --");
​
    System.out.println(tp.getSchemaAfterStep(i));
}
Available transformations and conversions
TransformProcess
​[source]​
A TransformProcess defines an ordered list of transformations to be executed on some data
getFinalSchema
public Schema getFinalSchema()
Get the action list that this transform process will execute
return
getSchemaAfterStep
public Schema getSchemaAfterStep(int step)
Return the schema after executing all steps up to and including the specified step. Steps are indexed from 0: so getSchemaAfterStep(0) is after one transform has been executed.
param step Index of the step
return Schema of the data, after that (and all prior) steps have been executed
toJson
public String toJson()
Execute the full sequence of transformations for a single example. May return null if example is filtered NOTE: Some TransformProcess operations cannot be done on examples individually. Most notably, ConvertToSequence and ConvertFromSequence operations require the full data set to be processed at once
param input
return
toYaml
public String toYaml()
Convert the TransformProcess to a YAML string
return TransformProcess, as YAML
fromJson
public static TransformProcess fromJson(String json)
Deserialize a JSON String (created by {- link #toJson()}) to a TransformProcess
return TransformProcess, from JSON
fromYaml
public static TransformProcess fromYaml(String yaml)
Deserialize a JSON String (created by {- link #toJson()}) to a TransformProcess
return TransformProcess, from JSON
transform
public Builder transform(Transform transform)
Infer the categories for the given record reader for a particular column Note that each “column index” is a column in the context of: List record = ...; record.get(columnIndex);
Note that anything passed in as a column will be automatically converted to a string for categorical purposes.
The expected input is strings or numbers (which have sensible toString() representations)
Note that the returned categories will be sorted alphabetically
param recordReader the record reader to iterate through
param columnIndex te column index to get categories for
return
filter
public Builder filter(Filter filter)
Add a filter operation to be executed after the previously-added operations have been executed
param filter Filter operation to execute
filter
public Builder filter(Condition condition)
Add a filter operation, based on the specified condition.
If condition is satisfied (returns true): remove the example or sequence
If condition is not satisfied (returns false): keep the example or sequence
param condition Condition to filter on
removeColumns
public Builder removeColumns(String... columnNames)
Remove all of the specified columns, by name
param columnNames Names of the columns to remove
removeColumns
public Builder removeColumns(Collection<String> columnNames)
Remove all of the specified columns, by name
param columnNames Names of the columns to remove
removeAllColumnsExceptFor
public Builder removeAllColumnsExceptFor(String... columnNames)
Remove all columns, except for those that are specified here
param columnNames Names of the columns to keep
removeAllColumnsExceptFor
public Builder removeAllColumnsExceptFor(Collection<String> columnNames)
Remove all columns, except for those that are specified here
param columnNames Names of the columns to keep
renameColumn
public Builder renameColumn(String oldName, String newName)
Rename a single column
param oldName Original column name
param newName New column name
renameColumns
public Builder renameColumns(List<String> oldNames, List<String> newNames)
Rename multiple columns
param oldNames List of original column names
param newNames List of new column names
reorderColumns
public Builder reorderColumns(String... newOrder)
Reorder the columns using a partial or complete new ordering. If only some of the column names are specified for the new order, the remaining columns will be placed at the end, according to their current relative ordering
param newOrder Names of the columns, in the order they will appear in the output
duplicateColumn
public Builder duplicateColumn(String column, String newName)
Duplicate a single column
param column Name of the column to duplicate
param newName Name of the new (duplicate) column
duplicateColumns
public Builder duplicateColumns(List<String> columnNames, List<String> newNames)
Duplicate a set of columns
param columnNames Names of the columns to duplicate
param newNames Names of the new (duplicated) columns
integerMathOp
public Builder integerMathOp(String column, MathOp mathOp, int scalar)
Perform a mathematical operation (add, subtract, scalar max etc) on the specified integer column, with a scalar
param column The integer column to perform the operation on
param mathOp The mathematical operation
param scalar The scalar value to use in the mathematical operation
integerColumnsMathOp
public Builder integerColumnsMathOp(String newColumnName, MathOp mathOp, String... columnNames)
Calculate and add a new integer column by performing a mathematical operation on a number of existing columns. New column is added to the end.
param newColumnName Name of the new/derived column
param mathOp Mathematical operation to execute on the columns
param columnNames Names of the columns to use in the mathematical operation
longMathOp
public Builder longMathOp(String columnName, MathOp mathOp, long scalar)
Perform a mathematical operation (add, subtract, scalar max etc) on the specified long column, with a scalar
param columnName The long column to perform the operation on
param mathOp The mathematical operation
param scalar The scalar value to use in the mathematical operation
longColumnsMathOp
public Builder longColumnsMathOp(String newColumnName, MathOp mathOp, String... columnNames)
Calculate and add a new long column by performing a mathematical operation on a number of existing columns. New column is added to the end.
param newColumnName Name of the new/derived column
param mathOp Mathematical operation to execute on the columns
param columnNames Names of the columns to use in the mathematical operation
floatMathOp
public Builder floatMathOp(String columnName, MathOp mathOp, float scalar)
Perform a mathematical operation (add, subtract, scalar max etc) on the specified double column, with a scalar
param columnName The float column to perform the operation on
param mathOp The mathematical operation
param scalar The scalar value to use in the mathematical operation
floatColumnsMathOp
public Builder floatColumnsMathOp(String newColumnName, MathOp mathOp, String... columnNames)
Calculate and add a new float column by performing a mathematical operation on a number of existing columns. New column is added to the end.
param newColumnName Name of the new/derived column
param mathOp Mathematical operation to execute on the columns
param columnNames Names of the columns to use in the mathematical operation
floatMathFunction
public Builder floatMathFunction(String columnName, MathFunction mathFunction)
Perform a mathematical operation (such as sin(x), ceil(x), exp(x) etc) on a column
param columnName Column name to operate on
param mathFunction MathFunction to apply to the column
doubleMathOp
public Builder doubleMathOp(String columnName, MathOp mathOp, double scalar)
Perform a mathematical operation (add, subtract, scalar max etc) on the specified double column, with a scalar
param columnName The double column to perform the operation on
param mathOp The mathematical operation
param scalar The scalar value to use in the mathematical operation
doubleColumnsMathOp
public Builder doubleColumnsMathOp(String newColumnName, MathOp mathOp, String... columnNames)
Calculate and add a new double column by performing a mathematical operation on a number of existing columns. New column is added to the end.
param newColumnName Name of the new/derived column
param mathOp Mathematical operation to execute on the columns
param columnNames Names of the columns to use in the mathematical operation
doubleMathFunction
public Builder doubleMathFunction(String columnName, MathFunction mathFunction)
Perform a mathematical operation (such as sin(x), ceil(x), exp(x) etc) on a column
param columnName Column name to operate on
param mathFunction MathFunction to apply to the column
timeMathOp
public Builder timeMathOp(String columnName, MathOp mathOp, long timeQuantity, TimeUnit timeUnit)
Perform a mathematical operation (add, subtract, scalar min/max only) on the specified time column
param columnName The integer column to perform the operation on
param mathOp The mathematical operation
param timeQuantity The quantity used in the mathematical op
param timeUnit The unit that timeQuantity is specified in
categoricalToOneHot
public Builder categoricalToOneHot(String... columnNames)
Convert the specified column(s) from a categorical representation to a one-hot representation. This involves the creation of multiple new columns each.
param columnNames Names of the categorical column(s) to convert to a one-hot representation
categoricalToInteger
public Builder categoricalToInteger(String... columnNames)
Convert the specified column(s) from a categorical representation to an integer representation. This will replace the specified categorical column(s) with an integer repreesentation, where each integer has the value 0 to numCategories-1.
param columnNames Name of the categorical column(s) to convert to an integer representation
integerToCategorical
public Builder integerToCategorical(String columnName, List<String> categoryStateNames)
Convert the specified column from an integer representation (assume values 0 to numCategories-1) to a categorical representation, given the specified state names
param columnName Name of the column to convert
param categoryStateNames Names of the states for the categorical column
integerToCategorical
public Builder integerToCategorical(String columnName, Map<Integer, String> categoryIndexNameMap)
Convert the specified column from an integer representation to a categorical representation, given the specified mapping between integer indexes and state names
param columnName Name of the column to convert
param categoryIndexNameMap Names of the states for the categorical column
integerToOneHot
public Builder integerToOneHot(String columnName, int minValue, int maxValue)
Convert an integer column to a set of 1 hot columns, based on the value in integer column
param columnName Name of the integer column
param minValue Minimum value possible for the integer column (inclusive)
param maxValue Maximum value possible for the integer column (inclusive)
addConstantColumn
public Builder addConstantColumn(String newColumnName, ColumnType newColumnType, Writable fixedValue)
Add a new column, where all values in the column are identical and as specified.
param newColumnName Name of the new column
param newColumnType Type of the new column
param fixedValue Value in the new column for all records
addConstantDoubleColumn
public Builder addConstantDoubleColumn(String newColumnName, double value)
Add a new double column, where the value for that column (for all records) are identical
param newColumnName Name of the new column
param value Value in the new column for all records
addConstantIntegerColumn
public Builder addConstantIntegerColumn(String newColumnName, int value)
Add a new integer column, where th e value for that column (for all records) are identical
param newColumnName Name of the new column
param value Value of the new column for all records
addConstantLongColumn
public Builder addConstantLongColumn(String newColumnName, long value)
Add a new integer column, where the value for that column (for all records) are identical
param newColumnName Name of the new column
param value Value in the new column for all records
convertToString
public Builder convertToString(String inputColumn)
Convert the specified column to a string.
param inputColumn the input column to convert
return builder pattern
convertToDouble
public Builder convertToDouble(String inputColumn)
Convert the specified column to a double.
param inputColumn the input column to convert
return builder pattern
convertToInteger
public Builder convertToInteger(String inputColumn)
Convert the specified column to an integer.
param inputColumn the input column to convert
return builder pattern
normalize
public Builder normalize(String column, Normalize type, DataAnalysis da)
Normalize the specified column with a given type of normalization
param column Column to normalize
param type Type of normalization to apply
param da DataAnalysis object
convertToSequence
public Builder convertToSequence(String keyColumn, SequenceComparator comparator)
Convert a set of independent records/examples into a sequence, according to some key. Within each sequence, values are ordered using the provided {- link SequenceComparator}
param keyColumn Column to use as a key (values with the same key will be combined into sequences)
param comparator A SequenceComparator to order the values within each sequence (for example, by time or String order)
convertToSequence
public Builder convertToSequence()
Convert a set of independent records/examples into a sequence; each example is simply treated as a sequence of length 1, without any join/group operations. Note that more commonly, joining/grouping is required; use {- link #convertToSequence(List, SequenceComparator)} for this functionality
convertToSequence
public Builder convertToSequence(List<String> keyColumns, SequenceComparator comparator)
Convert a set of independent records/examples into a sequence, where each sequence is grouped according to one or more key values (i.e., the values in one or more columns) Within each sequence, values are ordered using the provided {- link SequenceComparator}
param keyColumns Column to use as a key (values with the same key will be combined into sequences)
param comparator A SequenceComparator to order the values within each sequence (for example, by time or String order)
convertFromSequence
public Builder convertFromSequence()
Convert a sequence to a set of individual values (by treating each value in each sequence as a separate example)
splitSequence
public Builder splitSequence(SequenceSplit split)
Split sequences into 1 or more other sequences. Used for example to split large sequences into a set of smaller sequences
param split SequenceSplit that defines how splits will occur
trimSequence
public Builder trimSequence(int numStepsToTrim, boolean trimFromStart)
SequenceTrimTranform removes the first or last N values in a sequence. Note that the resulting sequence may be of length 0, if the input sequence is less than or equal to N.
param numStepsToTrim Number of time steps to trim from the sequence
param trimFromStart If true: Trim values from the start of the sequence. If false: trim values from the end.
offsetSequence
public Builder offsetSequence(List<String> columnsToOffset, int offsetAmount,
                                      SequenceOffsetTransform.OperationType operationType)
Perform a sequence of operation on the specified columns. Note that this also truncates sequences by the specified offset amount by default. Use {- code transform(new SequenceOffsetTransform(…)} to change this. See {- link SequenceOffsetTransform} for details on exactly what this operation does and how.
param columnsToOffset Columns to offset
param offsetAmount Amount to offset the specified columns by (positive offset: ‘columnsToOffset’ are moved to later time steps)
param operationType Whether the offset should be done in-place or by adding a new column
reduce
public Builder reduce(IAssociativeReducer reducer)
Reduce (i.e., aggregate/combine) a set of examples (typically by key). Note: In the current implementation, reduction operations can be performed only on standard (i.e., non-sequence) data
param reducer Reducer to use
reduceSequence
public Builder reduceSequence(IAssociativeReducer reducer)
Reduce (i.e., aggregate/combine) a set of sequence examples - for each sequence individually. Note: This method results in non-sequence data. If you would instead prefer sequences of length 1 after the reduction, use {- code transform(new ReduceSequenceTransform(reducer))}.
param reducer Reducer to use to reduce each window
reduceSequenceByWindow
public Builder reduceSequenceByWindow(IAssociativeReducer reducer, WindowFunction windowFunction)
Reduce (i.e., aggregate/combine) a set of sequence examples - for each sequence individually - using a window function. For example, take all records/examples in each 24-hour period (i.e., using window function), and convert them into a singe value (using the reducer). In this example, the output is a sequence, with time period of 24 hours.
param reducer Reducer to use to reduce each window
param windowFunction Window function to find apply on each sequence individually
sequenceMovingWindowReduce
public Builder sequenceMovingWindowReduce(String columnName, int lookback, ReduceOp op)
SequenceMovingWindowReduceTransform: Adds a new column, where the value is derived by:
(a) using a window of the last N values in a single column,
(b) Apply a reduction op on the window to calculate a new value
for example, this transformer can be used to implement a simple moving average of the last N values, or determine the minimum or maximum values in the last N time steps.
For example, for a simple moving average, length 20: {- code new SequenceMovingWindowReduceTransform(“myCol”, 20, ReduceOp.Mean)}
param columnName Column name to perform windowing on
param lookback Look back period for windowing
param op Reduction operation to perform on each window
calculateSortedRank
public Builder calculateSortedRank(String newColumnName, String sortOnColumn, WritableComparator comparator)
CalculateSortedRank: calculate the rank of each example, after sorting example. For example, we might have some numerical “score” column, and we want to know for the rank (sort order) for each example, according to that column.
The rank of each example (after sorting) will be added in a new Long column. Indexing is done from 0; examples will have values 0 to dataSetSize-1.
Currently, CalculateSortedRank can only be applied on standard (i.e., non-sequence) data Furthermore, the current implementation can only sort on one column
param newColumnName Name of the new column (will contain the rank for each example)
param sortOnColumn Column to sort on
param comparator Comparator used to sort examples
calculateSortedRank
public Builder calculateSortedRank(String newColumnName, String sortOnColumn, WritableComparator comparator,
                                           boolean ascending)
CalculateSortedRank: calculate the rank of each example, after sorting example. For example, we might have some numerical “score” column, and we want to know for the rank (sort order) for each example, according to that column.
The rank of each example (after sorting) will be added in a new Long column. Indexing is done from 0; examples will have values 0 to dataSetSize-1.
Currently, CalculateSortedRank can only be applied on standard (i.e., non-sequence) data Furthermore, the current implementation can only sort on one column
param newColumnName Name of the new column (will contain the rank for each example)
param sortOnColumn Column to sort on
param comparator Comparator used to sort examples
param ascending If true: sort ascending. False: descending
stringToCategorical
public Builder stringToCategorical(String columnName, List<String> stateNames)
Convert the specified String column to a categorical column. The state names must be provided.
param columnName Name of the String column to convert to categorical
param stateNames State names of the category
stringRemoveWhitespaceTransform
public Builder stringRemoveWhitespaceTransform(String columnName)
Remove all whitespace characters from the values in the specified String column
param columnName Name of the column to remove whitespace from
stringMapTransform
public Builder stringMapTransform(String columnName, Map<String, String> mapping)
Replace one or more String values in the specified column with new values.
Keys in the map are the original values; the Values in the map are their replacements. If a String appears in the data but does not appear in the provided map (as a key), that String values will not be modified.
param columnName Name of the column in which to do replacement
param mapping Map of oldValues -> newValues
stringToTimeTransform
public Builder stringToTimeTransform(String column, String format, DateTimeZone dateTimeZone)
Convert a String column (containing a date/time String) to a time column (by parsing the date/time String)
param column String column containing the date/time Strings
param format Format of the strings. Time format is specified as per http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html​
param dateTimeZone Timezone of the column
stringToTimeTransform
public Builder stringToTimeTransform(String column, String format, DateTimeZone dateTimeZone, Locale locale)
Convert a String column (containing a date/time String) to a time column (by parsing the date/time String)
param column String column containing the date/time Strings
param format Format of the strings. Time format is specified as per http://www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html​
param dateTimeZone Timezone of the column
param locale Locale of the column
appendStringColumnTransform
public Builder appendStringColumnTransform(String column, String toAppend)
Append a String to a specified column
param column Column to append the value to
param toAppend String to append to the end of each writable
conditionalReplaceValueTransform
public Builder conditionalReplaceValueTransform(String column, Writable newValue, Condition condition)
Replace the values in a specified column with a specified new value, if some condition holds. If the condition does not hold, the original values are not modified.
param column Column to operate on
param newValue Value to use as replacement, if condition is satisfied
param condition Condition that must be satisfied for replacement
conditionalReplaceValueTransformWithDefault
public Builder conditionalReplaceValueTransformWithDefault(String column, Writable yesVal, Writable noVal, Condition condition)
Replace the values in a specified column with a specified “yes” value, if some condition holds. Replace it with a “no” value, otherwise.
param column Column to operate on
param yesVal Value to use as replacement, if condition is satisfied
param noVal Value to use as replacement, if condition is not satisfied
param condition Condition that must be satisfied for replacement
conditionalCopyValueTransform
public Builder conditionalCopyValueTransform(String columnToReplace, String sourceColumn, Condition condition)
Replace the value in a specified column with a new value taken from another column, if a condition is satisfied/true.
Note that the condition can be any generic condition, including on other column(s), different to the column that will be modified if the condition is satisfied/true.
param columnToReplace Name of the column in which values will be replaced (if condition is satisfied)
param sourceColumn Name of the column from which the new values will be
param condition Condition to use
replaceStringTransform
public Builder replaceStringTransform(String columnName, Map<String, String> mapping)
Replace one or more String values in the specified column that match regular expressions.
Keys in the map are the regular expressions; the Values in the map are their String replacements. For example:
Original
Regex
Replacement
Result
Data_Vec
_
​
DataVec
B1C2T3
\d
one
BoneConeTone
'  4.25 '
^\s+|\s+$
​
'4.25'
param columnName Name of the column in which to do replacement
param mapping Map of old values or regular expression to new values
ndArrayScalarOpTransform
public Builder ndArrayScalarOpTransform(String columnName, MathOp op, double value)
Element-wise NDArray math operation (add, subtract, etc) on an NDArray column
param columnName Name of the NDArray column to perform the operation on
param op Operation to perform
param value Value for the operation
ndArrayColumnsMathOpTransform
public Builder ndArrayColumnsMathOpTransform(String newColumnName, MathOp mathOp, String... columnNames)
Perform an element wise mathematical operation (such as add, subtract, multiply) on NDArray columns. The existing columns are unchanged, a new NDArray column is added
param newColumnName Name of the new NDArray column
param mathOp Operation to perform
param columnNames Name of the columns used as input to the operation
ndArrayMathFunctionTransform
public Builder ndArrayMathFunctionTransform(String columnName, MathFunction mathFunction)
Apply an element wise mathematical function (sin, tanh, abs etc) to an NDArray column. This operation is performed in place.
param columnName Name of the column to perform the operation on
param mathFunction Mathematical function to apply
ndArrayDistanceTransform
public Builder ndArrayDistanceTransform(String newColumnName, Distance distance, String firstCol,
                                                String secondCol)
Calculate a distance (cosine similarity, Euclidean, Manhattan) on two equal-sized NDArray columns. This operation adds a new Double column (with the specified name) with the result.
param newColumnName Name of the new column (result) to add
param distance Distance to apply
param firstCol first column to use in the distance calculation
param secondCol second column to use in the distance calculation
firstDigitTransform
public Builder firstDigitTransform(String inputColumn, String outputColumn)
FirstDigitTransform converts a column to a categorical column, with values being the first digit of the number.
For example, “3.1415” becomes “3” and “2.0” becomes “2”.
Negative numbers ignore the sign: “-7.123” becomes “7”.
Note that two {- link FirstDigitTransform.Mode}s are supported, which determines how non-numerical entries should be handled:
EXCEPTION_ON_INVALID: output has 10 category values (“0”, …, “9”), and any non-numerical values result in an exception
INCLUDE_OTHER_CATEGORY: output has 11 category values (“0”, …, “9”, “Other”), all non-numerical values are mapped to “Other”
FirstDigitTransform is useful (combined with {- link CategoricalToOneHotTransform} and Reductions) to implement Benford’s law.
param inputColumn Input column name
param outputColumn Output column name. If same as input, input column is replaced
firstDigitTransform
public Builder firstDigitTransform(String inputColumn, String outputColumn, FirstDigitTransform.Mode mode)
FirstDigitTransform converts a column to a categorical column, with values being the first digit of the number.
For example, “3.1415” becomes “3” and “2.0” becomes “2”.
Negative numbers ignore the sign: “-7.123” becomes “7”.
Note that two {- link FirstDigitTransform.Mode}s are supported, which determines how non-numerical entries should be handled:
EXCEPTION_ON_INVALID: output has 10 category values (“0”, …, “9”), and any non-numerical values result in an exception
INCLUDE_OTHER_CATEGORY: output has 11 category values (“0”, …, “9”, “Other”), all non-numerical values are mapped to “Other”
FirstDigitTransform is useful (combined with {- link CategoricalToOneHotTransform} and Reductions) to implement Benford’s law.
param inputColumn Input column name
param outputColumn Output column name. If same as input, input column is replaced
param mode See {- link FirstDigitTransform.Mode}
build
public TransformProcess build()
Create the TransformProcess object
CategoricalToIntegerTransform
​[source]​
Created by Alex on 4/03/2016.
map
public Object map(Object input)
Transform an object in to another object
param input the record to transform
return the transformed writable
mapSequence
public Object mapSequence(Object sequence)
Transform a sequence
param sequence
outputColumnName
public String outputColumnName()
The output column name after the operation has been applied
return the output column name
columnName
public String columnName()
The output column names This will often be the same as the input
return the output column names
CategoricalToOneHotTransform
​[source]​
Created by Alex on 4/03/2016.
map
public Object map(Object input)
Transform an object in to another object
param input the record to transform
return the transformed writable
mapSequence
public Object mapSequence(Object sequence)
Transform a sequence
param sequence
outputColumnName
public String outputColumnName()
The output column name after the operation has been applied
return the output column name
columnName
public String columnName()
The output column names This will often be the same as the input
return the output column names
IntegerToCategoricalTransform
​[source]​
map
public Object map(Object input)
Transform an object in to another object
param input the record to transform
return the transformed writable
mapSequence
public Object mapSequence(Object sequence)
Transform a sequence
param sequence
PivotTransform
​[source]​
Pivot transform operates on two columns:
a categorical column that operates as a key, and
Another column that contains a value Essentially, Pivot transform takes keyvalue pairs and breaks them out into separate columns.
For example, with schema [col0, key, value, col3] and values with key in {a,b,c} Output schema is [col0, key[a], key[b], key[c], col3] and input (col0Val, b, x, col3Val) gets mapped to (col0Val, 0, x, 0, col3Val).
When expanding columns, a default value is used - for example 0 for numerical columns.
transform
public Schema transform(Schema inputSchema)
param keyColumnName Key column to expand
param valueColumnName Name of the column that contains the value
Original	Regex	Replacement	Result
Data_Vec	_		DataVec
B1C2T3	\d	one	BoneConeTone
' 4.25 '	^\s+\|\s+$		'4.25'