Serializable
, org.apache.spark.internal.Logging
, Params
, HasHandleInvalid
, HasInputCol
, DefaultParamsWritable
, Identifiable
, MLWritable
Note: VectorSizeHint modifies inputCol
to include size metadata and does not have an outputCol.
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
Constructors
Creates a copy of this instance with the same UID and some extra params.
int
Param for how to handle invalid entries.
Param for input column name.
The size of Vectors in inputCol
.
Transforms the input dataset.
Check transform validity and derive the output schema from the input schema.
An immutable unique ID for the object and its derivatives.
Methods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
Methods inherited from interface org.apache.spark.ml.util.MLWritablesave
Methods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
public VectorSizeHint()
Param for input column name.
inputCol
in interface HasInputCol
An immutable unique ID for the object and its derivatives.
uid
in interface Identifiable
The size of Vectors in inputCol
.
public int getSize()
group getParam
Param for how to handle invalid entries. Invalid vectors include nulls and vectors with the wrong size. The options are
skip
(filter out rows with invalid vectors),
error
(throw an error) and
optimistic
(do not check the vector size, and keep all rows).
error
by default.
Note: Users should take care when setting this param to optimistic
. The use of the optimistic
option will prevent the transformer from validating the sizes of vectors in inputCol
. A mismatch between the metadata of a column and its contents could result in unexpected behaviour or errors when using that column.
handleInvalid
in interface HasHandleInvalid
Transforms the input dataset.
transform
in class Transformer
dataset
- (undocumented)
Check transform validity and derive the output schema from the input schema.
We check validity for interactions between parameters during transformSchema
and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)
Params
Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy()
.
copy
in interface Params
copy
in class Transformer
extra
- (undocumented)
toString
in interface Identifiable
toString
in class Object
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