3859cc8699
* fix: deduplicate doc counts in term aggregation for multi-valued fields Term aggregation was counting term occurrences instead of documents for multi-valued fields. A document with the same value appearing multiple times would inflate doc_count. Add `fetch_block_with_missing_unique_per_doc` to ColumnBlockAccessor that deduplicates (doc_id, value) pairs, and use it in term aggregation. Fixes #2721 * refactor: only deduplicate for multivalue cardinality Duplicates can only occur with multivalue columns, so narrow the check from !is_full() to is_multivalue(). * fix: handle non-consecutive duplicate values in dedup Sort values within each doc_id group before deduplicating, so that non-adjacent duplicates are correctly handled. Add unit tests for dedup_docid_val_pairs: consecutive duplicates, non-consecutive duplicates, multi-doc groups, no duplicates, and single element. * perf: skip dedup when block has no multivalue entries Add early return when no consecutive doc_ids are equal, avoiding unnecessary sort and dedup passes. Remove the 2-element swap optimization as it is not needed by the dedup algorithm. --------- Co-authored-by: nryoo <nryoo@nryooui-MacBookPro.local>
Columnar format
This crate describes columnar format used in tantivy.
Goals
This format is special in the following way.
- it needs to be compact
- accessing a specific column does not require to load the entire columnar. It can be done in 2 to 3 random access.
- columns of several types can be associated with the same column name.
- it needs to support columns with different types
(str, u64, i64, f64)and different cardinality(required, optional, multivalued). - columns, once loaded, offer cheap random access.
- it is designed to allow range queries.
Coercion rules
Users can create a columnar by inserting rows to a ColumnarWriter,
and serializing it into a Write object.
Nothing prevents a user from recording values with different type to the same column_name.
In that case, tantivy-columnar's behavior is as follows:
- JsonValues are grouped into 3 types (String, Number, bool).
Values that corresponds to different groups are mapped to different columns. For instance, String values are treated independently
from Number or boolean values.
tantivy-columnarwill simply emit several columns associated to a given column_name. - Only one column for a given json value type is emitted. If number values with different number types are recorded (e.g. u64, i64, f64),
tantivy-columnarwill pick the first type that can represents the set of appended value, with the following prioriy order (i64,u64,f64).i64is picked overu64as it is likely to yield less change of types. Most use cases strictly requiringu64show the restriction on 50% of the values (e.g. a 64-bit hash). On the other hand, a lot of use cases can show rare negative value.
Columnar format
This columnar format may have more than one column (with different types) associated to the same column_name (see Coercion rules above).
The (column_name, column_type) couple however uniquely identifies a column.
That couple is serialized as a column column_key. The format of that key is:
[column_name][ZERO_BYTE][column_type_header: u8]
COLUMNAR:=
[COLUMNAR_DATA]
[COLUMNAR_KEY_TO_DATA_INDEX]
[COLUMNAR_FOOTER];
# Columns are sorted by their column key.
COLUMNAR_DATA:=
[COLUMN_DATA]+;
COLUMNAR_FOOTER := [RANGE_SSTABLE_BYTES_LEN: 8 bytes little endian]
The columnar file starts by the actual column data, concatenated one after the other, sorted by column key.
A sstable associates `(column name, column_cardinality, column_type) to range of bytes.
Column name may not contain the zero byte \0.
Listing all columns associated to column_name can therefore
be done by listing all keys prefixed by
[column_name][ZERO_BYTE]
The associated range of bytes refer to a range of bytes
This crate exposes a columnar format for tantivy. This format is described in README.md
The crate introduces the following concepts.
Columnar is an equivalent of a dataframe.
It maps column_key to Column.
A Column<T> associates a RowId (u32) to any
number of values.
This is made possible by wrapping a ColumnIndex and a ColumnValue object.
The ColumnValue<T> represents a mapping that associates each RowId to
exactly one single value.
The ColumnIndex then maps each RowId to a set of RowId in the
ColumnValue.
For optimization, and compression purposes, the ColumnIndex has three
possible representation, each for different cardinalities.
- Full
All RowId have exactly one value. The ColumnIndex is the trivial mapping.
- Optional
All RowIds can have at most one value. The ColumnIndex is the trivial mapping ColumnRowId -> Option<ColumnValueRowId>.
- Multivalued
All RowIds can have any number of values. The column index is mapping values to a range.
All these objects are implemented an unit tested independently in their own module:
- columnar
- column_index
- column_values
- column