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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 -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org