abstract class ColumnVector extends AutoCloseable
An interface representing in-memory columnar data in Spark. This interface defines the main APIs to access the data, as well as their batched versions. The batched versions are considered to be faster and preferable whenever possible.
Most of the APIs take the rowId as a parameter. This is the batch local 0-based row id for values in this ColumnVector.
Spark only calls specific get
method according to the data type of this
ColumnVector
,
e.g. if it's int type, Spark is guaranteed to only call #getInt(int)
or
int)
.
ColumnVector supports all the data types including nested types. To handle nested types,
ColumnVector can have children and is a tree structure. Please refer to #getStruct(int)
,
#getArray(int)
and #getMap(int)
for the details about how to implement nested
types.
ColumnVector is expected to be reused during the entire data loading process, to avoid allocating memory again and again.
ColumnVector is meant to maximize CPU efficiency but not to minimize storage footprint. Implementations should prefer computing efficiency over storage efficiency when design the format. Since it is expected to reuse the ColumnVector instance while loading data, the storage footprint is negligible.
- Annotations
- @Evolving()
- Source
- ColumnVector.java
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Instance Constructors
- new ColumnVector(type: DataType)
- Attributes
- protected[vectorized]
Abstract Value Members
- abstract def close(): Unit
Cleans up memory for this column vector.
Cleans up memory for this column vector. The column vector is not usable after this.
This overwrites
AutoCloseable#close
to remove thethrows
clause, as column vector is in-memory and we don't expect any exception to happen during closing.- Definition Classes
- ColumnVector → AutoCloseable
- Annotations
- @Override()
- abstract def getArray(rowId: Int): ColumnarArray
Returns the array type value for
rowId
.Returns the array type value for
rowId
. If the slot forrowId
is null, it should return null.To support array type, implementations must construct an
ColumnarArray
and return it in this method.ColumnarArray
requires aColumnVector
that stores the data of all the elements of all the arrays in this vector, and an offset and length which points to a range in thatColumnVector
, and the range represents the array for rowId. Implementations are free to decide where to put the data vector and offsets and lengths. For example, we can use the first child vector as the data vector, and store offsets and lengths in 2 int arrays in this vector. - abstract def getBinary(rowId: Int): Array[Byte]
Returns the binary type value for
rowId
.Returns the binary type value for
rowId
. If the slot forrowId
is null, it should return null. - abstract def getBoolean(rowId: Int): Boolean
Returns the boolean type value for
rowId
.Returns the boolean type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getByte(rowId: Int): Byte
Returns the byte type value for
rowId
.Returns the byte type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getChild(ordinal: Int): ColumnVector
- returns
child
ColumnVector
at the given ordinal.
- abstract def getDecimal(rowId: Int, precision: Int, scale: Int): Decimal
Returns the decimal type value for
rowId
.Returns the decimal type value for
rowId
. If the slot forrowId
is null, it should return null. - abstract def getDouble(rowId: Int): Double
Returns the double type value for
rowId
.Returns the double type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getFloat(rowId: Int): Float
Returns the float type value for
rowId
.Returns the float type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getInt(rowId: Int): Int
Returns the int type value for
rowId
.Returns the int type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getLong(rowId: Int): Long
Returns the long type value for
rowId
.Returns the long type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getMap(ordinal: Int): ColumnarMap
Returns the map type value for
rowId
.Returns the map type value for
rowId
. If the slot forrowId
is null, it should return null.In Spark, map type value is basically a key data array and a value data array. A key from the key array with a index and a value from the value array with the same index contribute to an entry of this map type value.
To support map type, implementations must construct a
ColumnarMap
and return it in this method.ColumnarMap
requires aColumnVector
that stores the data of all the keys of all the maps in this vector, and anotherColumnVector
that stores the data of all the values of all the maps in this vector, and a pair of offset and length which specify the range of the key/value array that belongs to the map type value at rowId. - abstract def getShort(rowId: Int): Short
Returns the short type value for
rowId
.Returns the short type value for
rowId
. The return value is undefined and can be anything, if the slot forrowId
is null. - abstract def getUTF8String(rowId: Int): UTF8String
Returns the string type value for
rowId
.Returns the string type value for
rowId
. If the slot forrowId
is null, it should return null.Note that the returned
UTF8String
may point to the data of this column vector, please copy it if you want to keep it after this column vector is freed. - abstract def hasNull(): Boolean
Returns true if this column vector contains any null values.
- abstract def isNullAt(rowId: Int): Boolean
Returns whether the value at
rowId
is NULL. - abstract def numNulls(): Int
Returns the number of nulls in this column vector.
Concrete Value Members
- final def !=(arg0: Any): Boolean
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- final def dataType(): DataType
Returns the data type of this column vector.
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def getBooleans(rowId: Int, count: Int): Array[Boolean]
Gets boolean type values from
[rowId, rowId + count)
.Gets boolean type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - def getBytes(rowId: Int, count: Int): Array[Byte]
Gets byte type values from
[rowId, rowId + count)
.Gets byte type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - final def getClass(): Class[_ <: AnyRef]
- Definition Classes
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- @IntrinsicCandidate() @native()
- def getDoubles(rowId: Int, count: Int): Array[Double]
Gets double type values from
[rowId, rowId + count)
.Gets double type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - def getFloats(rowId: Int, count: Int): Array[Float]
Gets float type values from
[rowId, rowId + count)
.Gets float type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - def getInterval(rowId: Int): CalendarInterval
Returns the calendar interval type value for
rowId
.Returns the calendar interval type value for
rowId
. If the slot forrowId
is null, it should return null.In Spark, calendar interval type value is basically two integer values representing the number of months and days in this interval, and a long value representing the number of microseconds in this interval. An interval type vector is the same as a struct type vector with 3 fields:
months
,days
andmicroseconds
.To support interval type, implementations must implement
#getChild(int)
and define 3 child vectors: the first child vector is an int type vector, containing all the month values of all the interval values in this vector. The second child vector is an int type vector, containing all the day values of all the interval values in this vector. The third child vector is a long type vector, containing all the microsecond values of all the interval values in this vector. Note that the ArrowColumnVector leverages its built-in IntervalMonthDayNanoVector instead of above-mentioned protocol. - def getInts(rowId: Int, count: Int): Array[Int]
Gets int type values from
[rowId, rowId + count)
.Gets int type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - def getLongs(rowId: Int, count: Int): Array[Long]
Gets long type values from
[rowId, rowId + count)
.Gets long type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - def getShorts(rowId: Int, count: Int): Array[Short]
Gets short type values from
[rowId, rowId + count)
.Gets short type values from
[rowId, rowId + count)
. The return values for the null slots are undefined and can be anything. - final def getStruct(rowId: Int): ColumnarRow
Returns the struct type value for
rowId
.Returns the struct type value for
rowId
. If the slot forrowId
is null, it should return null.To support struct type, implementations must implement
#getChild(int)
and make this vector a tree structure. The number of child vectors must be same as the number of fields of the struct type, and each child vector is responsible to store the data for its corresponding struct field. - final def getVariant(rowId: Int): VariantVal
Returns the Variant value for
rowId
.Returns the Variant value for
rowId
. Similar to#getInterval(int)
, the implementation must implement#getChild(int)
and define 2 child vectors of binary type for the Variant value and metadata. - def hashCode(): Int
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- Deprecated
(Since version 9)