issue: https://github.com/milvus-io/milvus/issues/27467
>My plan is as follows.
>- [x] M1 Create collection with timestamptz field
>- [x] M2 Insert timestamptz field data
>- [x] M3 Retrieve timestamptz field data
>- [x] M4 Implement handoff
>- [x] M5 Implement compare operator
>- [x] M6 Implement extract operator
>- [x] M8 Support database/collection level default timezone
>- [x] M7 Support STL-SORT index for datatype timestamptz
---
The third PR of issue: https://github.com/milvus-io/milvus/issues/27467,
which completes M5, M6, M7, M8 described above.
## M8 Default Timezone
We will be able to use alter_collection() and alter_database() in a
future Python SDK release to modify the default timezone at the
collection or database level.
For insert requests, the timezone will be resolved using the following
order of precedence: String Literal-> Collection Default -> Database
Default.
For retrieval requests, the timezone will be resolved in this order:
Query Parameters -> Collection Default -> Database Default.
In both cases, the final fallback timezone is UTC.
## M5: Comparison Operators
We can now use the following expression format to filter on the
timestamptz field:
- `timestamptz_field [+/- INTERVAL 'interval_string'] {comparison_op}
ISO 'iso_string' `
- The interval_string follows the ISO 8601 duration format, for example:
P1Y2M3DT1H2M3S.
- The iso_string follows the ISO 8601 timestamp format, for example:
2025-01-03T00:00:00+08:00.
- Example expressions: "tsz + INTERVAL 'P0D' != ISO
'2025-01-03T00:00:00+08:00'" or "tsz != ISO
'2025-01-03T00:00:00+08:00'".
## M6: Extract
We will be able to extract sepecific time filed by kwargs in a future
Python SDK release.
The key is `time_fields`, and value should be one or more of "year,
month, day, hour, minute, second, microsecond", seperated by comma or
space. Then the result of each record would be an array of int64.
## M7: Indexing Support
Expressions without interval arithmetic can be accelerated using an
STL-SORT index. However, expressions that include interval arithmetic
cannot be indexed. This is because the result of an interval calculation
depends on the specific timestamp value. For example, adding one month
to a date in February results in a different number of added days than
adding one month to a date in March.
---
After this PR, the input / output type of timestamptz would be iso
string. Timestampz would be stored as timestamptz data, which is int64_t
finally.
> for more information, see https://en.wikipedia.org/wiki/ISO_8601
---------
Signed-off-by: xtx <xtianx@smail.nju.edu.cn>
issue: https://github.com/milvus-io/milvus/issues/32262
The old implementation always takes metric type from the first sub
result, which may not always be valid. The fixed implementation returns
initialized metric type from sub results.
Signed-off-by: smdsbz <smdsbz@qq.com>
Ref https://github.com/milvus-io/milvus/issues/42148
This PR supports create index for vector array (now, only for
`DataType.FLOAT_VECTOR`) and search on it.
The index type supported in this PR is `EMB_LIST_HNSW` and the metric
type is `MAX_SIM` only.
The way to use it:
```python
milvus_client = MilvusClient("xxx:19530")
schema = milvus_client.create_schema(enable_dynamic_field=True, auto_id=True)
...
struct_schema = milvus_client.create_struct_array_field_schema("struct_array_field")
...
struct_schema.add_field("struct_float_vec", DataType.ARRAY_OF_VECTOR, element_type=DataType.FLOAT_VECTOR, dim=128, max_capacity=1000)
...
schema.add_struct_array_field(struct_schema)
index_params = milvus_client.prepare_index_params()
index_params.add_index(field_name="struct_float_vec", index_type="EMB_LIST_HNSW", metric_type="MAX_SIM", index_params={"nlist": 128})
...
milvus_client.create_index(COLLECTION_NAME, schema=schema, index_params=index_params)
```
Note: This PR uses `Lims` to convey offsets of the vector array to
knowhere where vectors of multiple vector arrays are concatenated and we
need offsets to specify which vectors belong to which vector array.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
See #36264
In this PR:
- Enhanced error handling in parse of grouping field.
- Fixed null handling in reduce tasks in proxy nodes.
- Updated tests to reflect changes in error handling and data processing
logic.
---------
Signed-off-by: Ted Xu <ted.xu@zilliz.com>
When delete by partition_key, Milvus will generates L0 segments
globally. During L0 Compaction, those L0 segments will touch all
partitions collection wise. Due to the false-positive rate of segment
bloomfilters, L0 compactions will append false deltalogs to completed
irrelevant partitions, which causes *partition deletion amplification.
This PR uses partition_key to set targeted partitionID when producing
deleteMsgs into MsgStreams. This'll narrow down L0 segments scope to
partition level, and remove the false-positive influence
collection-wise.
However, due to DeleteMsg structure, we can only label one partition to
one deleteMsg, so this enhancement fails if user wants to delete over 2
partition_keys in one deletion.
See also: #34665
Signed-off-by: yangxuan <xuan.yang@zilliz.com>
fix not append valid data when transfer to insert record and add a tiny
check when in groupBy field.
#35924
Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
issue: #29892
This PR
1. Pass Materialized View (MV) search information obtained from the
expression parsing planning procedure to Knowhere. It only performs when
MV is enabled and the partition key is involved in the expression. The
search information includes:
1. Touched field_id and the count of related categories in the
expression. E.g., `color == red && color == blue` yields `field_id ->
2`.
2. Whether the expression only includes AND (&&) logical operator,
default `true`.
3. Whether the expression has NOT (!) operator, default `false`.
4. Store if turning on MV on the proxy to eliminate reading from
paramtable for every search request.
5. Renames to MV.
## Rebuttals
1. Did not write in `ExtractInfoPlanNodeVisitor` since the new scalar
framework was introduced and this part might be removed in the future.
2. Currently only interested in `==` and `in` expression, `string` data
type, anything else is a bonus.
3. Leave handling expressions like `F == A || F == A` for future works
of the optimizer.
## Detailed MV Info
Signed-off-by: Patrick Weizhi Xu <weizhi.xu@zilliz.com>
