Uses of Class
ai.rapids.cudf.DType

Uses of DType in ai.rapids.cudf

Methods in ai.rapids.cudf that return DType

Modifier and Type	Method and Description
static DType	DType.fromNative(int nativeId)
DType	JCudfSerialization.SerializedTableHeader.getColumnType(int columnIndex)
DType	ColumnVector.OffHeapState.getNativeType()
DType	BinaryOperable.getType() Get the type of this data.
DType	HostColumnVector.getType() Returns the type of this vector.
DType	ColumnVector.getType() Returns the type of this vector.
DType	Scalar.getType()
static DType	BinaryOperable.implicitConversion(BinaryOperable lhs, BinaryOperable rhs) Finds the proper DType for an implicit output.
static DType	DType.valueOf(String name) Returns the enum constant of this type with the specified name.
static DType[]	DType.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in ai.rapids.cudf with parameters of type DType

Modifier and Type	Method and Description
default ColumnVector	BinaryOperable.add(BinaryOperable rhs, DType outType) Add + operator.
Scalar	ColumnVector.all(DType outType) Returns a scalar is true or 1, depending on the specified type, if all of the elements in the column are true or non-zero otherwise false or 0.
default ColumnVector	BinaryOperable.and(BinaryOperable rhs, DType outType) Logical and (&&) with the given output type.
Scalar	ColumnVector.any(DType outType) Returns a scalar is true or 1, depending on the specified type, if any of the elements in the column are true or non-zero otherwise false or 0.
default ColumnVector	BinaryOperable.arctan2(BinaryOperable xCoordinate, DType outType) The function arctan2(y,x) or atan2(y,x) is defined as the angle in the Euclidean plane, given in radians, between the positive x axis and the ray to the point (x, y) ≠ (0, 0).
ColumnVector	ColumnVector.asTimestamp(DType timestampType, String format) Parse a string to a timestamp.
ColumnVector	BinaryOperable.binaryOp(BinaryOp op, BinaryOperable rhs, DType outType) Multiple different binary operations.
ColumnVector	ColumnVector.binaryOp(BinaryOp op, BinaryOperable rhs, DType outType) Multiple different binary operations.
ColumnVector	Scalar.binaryOp(BinaryOp op, BinaryOperable rhs, DType outType)
default ColumnVector	BinaryOperable.bitAnd(BinaryOperable rhs, DType outType) Bit wise and (&) with the given output type.
default ColumnVector	BinaryOperable.bitOr(BinaryOperable rhs, DType outType) Bit wise or (|) with the given output type.
default ColumnVector	BinaryOperable.bitXor(BinaryOperable rhs, DType outType) Bit wise xor (^) with the given output type.
static HostColumnVector	HostColumnVector.build(DType type, int rows, java.util.function.Consumer<HostColumnVector.Builder> init) Create a new vector.
static ColumnVector	ColumnVector.build(DType type, int rows, java.util.function.Consumer<HostColumnVector.Builder> init) Create a new vector.
static HostColumnVector.Builder	HostColumnVector.builder(DType type, int rows) Create a new Builder to hold the specified number of rows.
ColumnVector	ColumnVector.castTo(DType type) Generic method to cast ColumnVector When casting from a Date, Timestamp, or Boolean to a numerical type the underlying numerical representation of the data will be used for the cast.
Schema.Builder	Schema.Builder.column(DType type, String name)
default ColumnVector	BinaryOperable.div(BinaryOperable rhs, DType outType) Divide one vector by another with the given output type.
default ColumnVector	BinaryOperable.equalTo(BinaryOperable rhs, DType outType) this == rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.equalToNullAware(BinaryOperable rhs, DType outType) like equalTo but NULL == NULL is TRUE and NULL == not NULL is FALSE
default ColumnVector	BinaryOperable.floorDiv(BinaryOperable rhs, DType outType) Divide one vector by another and calculate the floor of the result with the given output type.
static Scalar	Scalar.fromNull(DType type)
default ColumnVector	BinaryOperable.greaterOrEqualTo(BinaryOperable rhs, DType outType) this >= rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.greaterThan(BinaryOperable rhs, DType outType) this > rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.lessOrEqualTo(BinaryOperable rhs, DType outType) this <= rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.lessThan(BinaryOperable rhs, DType outType) this < rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.log(BinaryOperable rhs, DType outType) Calculate the log with the specified base
Scalar	ColumnVector.max(DType outType) Returns the maximum of all values in the column, returning a scalar of the specified type.
default ColumnVector	BinaryOperable.maxNullAware(BinaryOperable rhs, DType outType) Returns the max non null value.
Scalar	ColumnVector.mean(DType outType) Returns the arithmetic mean of all values in the column, returning a scalar of the specified type.
Scalar	ColumnVector.min(DType outType) Returns the minimum of all values in the column, returning a scalar of the specified type.
default ColumnVector	BinaryOperable.minNullAware(BinaryOperable rhs, DType outType) Returns the min non null value.
default ColumnVector	BinaryOperable.mod(BinaryOperable rhs, DType outType) Compute the modulus with the given output type.
default ColumnVector	BinaryOperable.mul(BinaryOperable rhs, DType outType) Multiply two vectors together with the given output type.
default ColumnVector	BinaryOperable.notEqualTo(BinaryOperable rhs, DType outType) this != rhs 1 is true 0 is false with the output cast to the given type.
default ColumnVector	BinaryOperable.or(BinaryOperable rhs, DType outType) Logical or (||) with the given output type.
default ColumnVector	BinaryOperable.pmod(BinaryOperable rhs, DType outputType) Returns the positive value of lhs mod rhs.
default ColumnVector	BinaryOperable.pow(BinaryOperable rhs, DType outType) Compute the power with the given output type.
Scalar	ColumnVector.product(DType outType) Returns the product of all values in the column, returning a scalar of the specified type.
Scalar	ColumnVector.reduce(ai.rapids.cudf.AggregateOp op, DType outType) Computes the reduction of the values in all rows of a column.
default ColumnVector	BinaryOperable.shiftLeft(BinaryOperable shiftBy, DType outType) Bitwise left shifts the values of this vector by shiftBy.
default ColumnVector	BinaryOperable.shiftRight(BinaryOperable shiftBy, DType outType) Bitwise right shift this vector by the shiftBy.
default ColumnVector	BinaryOperable.shiftRightUnsigned(BinaryOperable shiftBy, DType outType) This method bitwise right shifts the values of this vector by the shiftBy.
Scalar	ColumnVector.standardDeviation(DType outType) Returns the sample standard deviation of all values in the column, returning a scalar of the specified type.
default ColumnVector	BinaryOperable.sub(BinaryOperable rhs, DType outType) Subtract one vector from another with the given output type.
Scalar	ColumnVector.sum(DType outType) Computes the sum of all values in the column, returning a scalar of the specified type.
Scalar	ColumnVector.sumOfSquares(DType outType) Returns the sum of squares of all values in the column, returning a scalar of the specified type.
static Scalar	Scalar.timestampFromLong(DType type, long value)
static Scalar	Scalar.timestampFromLong(DType type, Long value)
default ColumnVector	BinaryOperable.trueDiv(BinaryOperable rhs, DType outType) Divide one vector by another converting to FLOAT64 in between with the given output type.
Scalar	ColumnVector.variance(DType outType) Returns the variance of all values in the column, returning a scalar of the specified type.
ORCOptions.Builder	ORCOptions.Builder.withTimeUnit(DType unit) Specify the time unit to use when returning timestamps.
ParquetOptions.Builder	ParquetOptions.Builder.withTimeUnit(DType unit) Specify the time unit to use when returning timestamps.

Constructors in ai.rapids.cudf with parameters of type DType

Constructor and Description
ColumnVector(DType type, long rows, Optional<Long> nullCount, DeviceMemoryBuffer dataBuffer, DeviceMemoryBuffer validityBuffer, DeviceMemoryBuffer offsetBuffer) Create a new column vector based off of data already on the device.
OffHeapState(DType type, int rows, Optional<Long> nullCount, DeviceMemoryBuffer data, DeviceMemoryBuffer valid, DeviceMemoryBuffer offsets) Create a cudf::column_view from device side data.