DataFrameStatFunctions¶
DataFrameStatFunctions
is used to work with <
[[methods]] .DataFrameStatFunctions API [cols="1,2",options="header",width="100%"] |=== | Method | Description
| <
[source, scala]¶
approxQuantile( cols: Array[String], probabilities: Array[Double], relativeError: Double): Array[Array[Double]] approxQuantile( col: String, probabilities: Array[Double], relativeError: Double): Array[Double]
| <
[source, scala]¶
bloomFilter(col: Column, expectedNumItems: Long, fpp: Double): BloomFilter bloomFilter(col: Column, expectedNumItems: Long, numBits: Long): BloomFilter bloomFilter(colName: String, expectedNumItems: Long, fpp: Double): BloomFilter bloomFilter(colName: String, expectedNumItems: Long, numBits: Long): BloomFilter
| <
[source, scala]¶
corr(col1: String, col2: String): Double corr(col1: String, col2: String, method: String): Double
| <
[source, scala]¶
countMinSketch(col: Column, eps: Double, confidence: Double, seed: Int): CountMinSketch countMinSketch(col: Column, depth: Int, width: Int, seed: Int): CountMinSketch countMinSketch(colName: String, eps: Double, confidence: Double, seed: Int): CountMinSketch countMinSketch(colName: String, depth: Int, width: Int, seed: Int): CountMinSketch
| <
[source, scala]¶
cov(col1: String, col2: String): Double¶
| <
[source, scala]¶
crosstab(col1: String, col2: String): DataFrame¶
| <
[source, scala]¶
freqItems(cols: Array[String]): DataFrame freqItems(cols: Array[String], support: Double): DataFrame freqItems(cols: Seq[String]): DataFrame freqItems(cols: Seq[String], support: Double): DataFrame
| <
[source, scala]¶
sampleByT: DataFrame¶
|===
[[creating-instance]] DataFrameStatFunctions
is available using stat untyped transformation.
[source, scala]¶
val q: DataFrame = ... q.stat
=== [[approxQuantile]] approxQuantile
Method
[source, scala]¶
approxQuantile( cols: Array[String], probabilities: Array[Double], relativeError: Double): Array[Array[Double]] approxQuantile( col: String, probabilities: Array[Double], relativeError: Double): Array[Double]
approxQuantile
...FIXME
=== [[bloomFilter]] bloomFilter
Method
[source, scala]¶
bloomFilter(col: Column, expectedNumItems: Long, fpp: Double): BloomFilter bloomFilter(col: Column, expectedNumItems: Long, numBits: Long): BloomFilter bloomFilter(colName: String, expectedNumItems: Long, fpp: Double): BloomFilter bloomFilter(colName: String, expectedNumItems: Long, numBits: Long): BloomFilter
bloomFilter
...FIXME
=== [[buildBloomFilter]] buildBloomFilter
Internal Method
[source, scala]¶
buildBloomFilter(col: Column, zero: BloomFilter): BloomFilter¶
buildBloomFilter
...FIXME
NOTE: convertToDouble
is used when...FIXME
=== [[corr]] corr
Method
[source, scala]¶
corr(col1: String, col2: String): Double corr(col1: String, col2: String, method: String): Double
corr
...FIXME
=== [[countMinSketch]] countMinSketch
Method
[source, scala]¶
countMinSketch(col: Column, eps: Double, confidence: Double, seed: Int): CountMinSketch countMinSketch(col: Column, depth: Int, width: Int, seed: Int): CountMinSketch countMinSketch(colName: String, eps: Double, confidence: Double, seed: Int): CountMinSketch countMinSketch(colName: String, depth: Int, width: Int, seed: Int): CountMinSketch // PRIVATE API countMinSketch(col: Column, zero: CountMinSketch): CountMinSketch
countMinSketch
...FIXME
=== [[cov]] cov
Method
[source, scala]¶
cov(col1: String, col2: String): Double¶
cov
...FIXME
=== [[crosstab]] crosstab
Method
[source, scala]¶
crosstab(col1: String, col2: String): DataFrame¶
crosstab
...FIXME
=== [[freqItems]] freqItems
Method
[source, scala]¶
freqItems(cols: Array[String]): DataFrame freqItems(cols: Array[String], support: Double): DataFrame freqItems(cols: Seq[String]): DataFrame freqItems(cols: Seq[String], support: Double): DataFrame
freqItems
...FIXME
=== [[sampleBy]] sampleBy
Method
[source, scala]¶
sampleByT: DataFrame¶
sampleBy
...FIXME