org.apache.spark.sql.execution.columnar
encoding
Run length encoding optimized for booleans.
Decodes the deleted positions of a batch that has seen some deletes.
Simple delta that merges the deleted positions
Currently just stores the deleted positions assuming sorted by position at plan level.
Currently just stores the deleted positions assuming sorted by position at plan level. This can be optimized to use a more efficient storage when number of positions is large large like a boolean bitset, or use a more comprehensive compression scheme like PFOR (https://github.com/lemire/JavaFastPFOR).
Internal class to decode values from a single delta as obtained from ColumnDeltaEncoder.
Internal class to decode values from a single delta as obtained from ColumnDeltaEncoder. Should not be used directly rather the combined decoder UpdatedColumnDecoder should be the one used.
Encodes a delta value for a ColumnFormatValue obtained after an update operation that can change one or more values.
Encodes a delta value for a ColumnFormatValue obtained after an update operation that can change one or more values. This applies the update in an optimized batch manner as far as possible.
The format of delta encoding is straightforward and adds the positions in the full column in addition to the normal column encoding. So the layout looks like below:
.----------------------- Base encoding scheme (4 bytes) | .------------------- Null bitset size as number of longs N (4 bytes) | | | | .---------------- Null bitset longs (8 x N bytes, | | | empty if null count is zero) | | | .------------- Positions in full column value | | | | | | | | .-------- Encoded non-null elements | | | | | V V V V V +---+---+--+--- +--------------+ | | | | | ... ... | +---+---+--+----+--------------+ \-----/ \--------------------/ header body
Whether the value type is a delta or not is determined by the "deltaHierarchy" field in ColumnFormatValue and the negative columnIndex in ColumnFormatKey. Encoding typeId itself does not store anything for it separately.
An alternative could be storing the position before each encoded element but it will not work properly for schemes like run-length encoding that will not write anything if elements are in that current run-length.
A set of new updated column values results in the merge of those values with the existing encoded values held in the current delta with smallest hierarchy depth (i.e. one that has a maximum size of 100). Each delta can grow to a limit after which it is subsumed in a larger delta of bigger size thus creating a hierarchy of deltas. So base delta will go till 100 entries or so, then the next higher level one will go till say 1000 entries and so on till the full ColumnFormatValue size is attained. This design attempts to minimize disk writes at the cost of some scan overhead for columns that see a large number of updates. The hierarchy is expected to be small not more than 3-4 levels to get a good balance between write overhead and scan overhead.
Base class for encoding and decoding in columnar form.
Base class for encoding and decoding in columnar form. Memory layout of the bytes for a set of column values is:
.----------------------- Encoding scheme (4 bytes) | .------------------- Null bitset size as number of longs N (4 bytes) | | | | .---------------- Null bitset longs (8 x N bytes, | | | empty if null count is zero) | | | .---------- Encoded non-null elements V V V V +---+---+-----+---------+ | | | ... | ... ... | +---+---+-----+---------+ \-----/ \-------------/ header body
Trait to read column values from delta encoded column and write to target delta column.
Trait to read column values from delta encoded column and write to target delta column. The reads may not be sequential and could be random-access reads while writes will be sequential, sorted by position in the full column value. Implementations should not do any null value handling.
This uses a separate base class rather than a closure to avoid the overhead of boxing/unboxing with multi-argument closures (>2 arguments).
Factory for DeltaWriter used by code generation to enable using the simpler Janino "createFastEvaluator" API.
Nulls are stored either as a bitset or as a sequence of positions (or inverse sequence of missing positions) if the number of nulls is small (or non-nulls is small).
Nulls are stored either as a bitset or as a sequence of positions (or inverse sequence of missing positions) if the number of nulls is small (or non-nulls is small). This is indicated by the count field which is negative for the latter case. The decoder for latter keeps track of next null position and compares against that.
Decodes a column of a batch that has seen some updates by combining all delta values, and full column value obtained from ColumnDeltaEncoders and column encoders.
Decodes a column of a batch that has seen some updates by combining all delta values, and full column value obtained from ColumnDeltaEncoders and column encoders. Callers should provide this with the set of all deltas for the column apart from the full column value.
To create an instance, use the companion class apply method which will create a nullable or non-nullable version as appropriate.
Nullable version of UpdatedColumnDecoder.
Static methods for working with fixed-size bitsets stored elsewhere in a byte array or long array.
Static methods for working with fixed-size bitsets stored elsewhere
in a byte array or long array. Similar to Spark's BitSetMethods
but respects platform endian-ness so is suitable for storage.
Run length encoding optimized for booleans. Each short run-length value represents the run-length with the value. Even numbered run-lengths indicate a run of false values having half the length, while odd numbered run-lengths are for true values (having length = run / 2 + 1).