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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2014/10/11 02:57:34 UTC
[jira] [Updated] (SPARK-3903) Create general data loading method
for LabeledPoints
[ https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-3903:
-------------------------------------
Description:
Proposal: Provide a more general data loading function for LabeledPoints.
* load multiple data files (e.g., train + test), and ensure they have the same number of features (determined based on a scan of the data)
* use same function for multiple input formats
Proposed function format (in MLUtils), with default parameters:
{code}
def loadLabeledPointsFiles(
sc: SparkContext,
paths: Seq[String],
numFeatures = -1,
vectorFormat = "auto",
numPartitions = sc.defaultMinPartitions): Seq[RDD[LabeledPoint]]
{code}
About the parameters:
* paths: list of paths to data files or folders with data files
* vectorFormat options: dense/sparse/auto
* numFeatures, numPartitions: same behavior as loadLibSVMFile
Return value: Order of RDDs follows the order of the paths.
Note: This is named differently from loadLabeledPoints for 2 reasons:
* different argument order (following loadLibSVMFile)
* different return type
was:
Proposal: Provide a more general data loading function for LabeledPoints.
* load multiple data files (e.g., train + test), and ensure they have the same number of features (determined based on a scan of the data)
* use same function for multiple input formats
Proposed function format (in MLUtils), with default parameters:
{code}
def loadLabeledPointsFiles(
sc: SparkContext,
paths: Seq[String],
numFeatures = -1,
vectorFormat = "auto",
numPartitions = sc.defaultMinPartitions): Seq[RDD[LabeledPoint]]
{code}
About the parameters:
* paths: list of paths to data files or folders with data files
* vectorFormat options: dense/sparse/auto
* numFeatures, numPartitions: same behavior as loadLibSVMFile
> Create general data loading method for LabeledPoints
> ----------------------------------------------------
>
> Key: SPARK-3903
> URL: https://issues.apache.org/jira/browse/SPARK-3903
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Joseph K. Bradley
> Priority: Minor
>
> Proposal: Provide a more general data loading function for LabeledPoints.
> * load multiple data files (e.g., train + test), and ensure they have the same number of features (determined based on a scan of the data)
> * use same function for multiple input formats
> Proposed function format (in MLUtils), with default parameters:
> {code}
> def loadLabeledPointsFiles(
> sc: SparkContext,
> paths: Seq[String],
> numFeatures = -1,
> vectorFormat = "auto",
> numPartitions = sc.defaultMinPartitions): Seq[RDD[LabeledPoint]]
> {code}
> About the parameters:
> * paths: list of paths to data files or folders with data files
> * vectorFormat options: dense/sparse/auto
> * numFeatures, numPartitions: same behavior as loadLibSVMFile
> Return value: Order of RDDs follows the order of the paths.
> Note: This is named differently from loadLabeledPoints for 2 reasons:
> * different argument order (following loadLibSVMFile)
> * different return type
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