feat: show timeseries [order by timseries] clause

Support ORDER BY TIMESERIES in SHOW TIMESERIES and Optimize OFFSET with Subtree Measurement Statistics

Brief

This PR introduces ordering support for SHOW TIMESERIES by measurement name (lexicographical) and optimizes the performance of the OFFSET clause using subtree measurement statistics.

Currently, SHOW TIMESERIES supports the ORDER BY TIMESERIES clause.
When the query scope is within a single database, OFFSET X no longer requires traversing the first X measurements one by one. Instead, it skips subtrees in the metadata tree based on subtree measurement counts.

Example:

IoTDB> show timeseries root.dbtest.** order by timeseries desc limit 5 offset 5001
+--------------------------------+-----+-----------+--------+--------+-----------+----+----------+--------+------------------+--------+
|                      Timeseries|Alias|   Database|DataType|Encoding|Compression|Tags|Attributes|Deadband|DeadbandParameters|ViewType|
+--------------------------------+-----+-----------+--------+--------+-----------+----+----------+--------+------------------+--------+
|root.dbtest.plant9.device84.m188| null|root.dbtest|   INT32|     RLE|     SNAPPY|null|      null|    null|              null|    BASE|
|root.dbtest.plant9.device84.m187| null|root.dbtest|   INT32|     RLE|     SNAPPY|null|      null|    null|              null|    BASE|
|root.dbtest.plant9.device84.m186| null|root.dbtest|   INT32|     RLE|     SNAPPY|null|      null|    null|              null|    BASE|
|root.dbtest.plant9.device84.m185| null|root.dbtest|   INT32|     RLE|     SNAPPY|null|      null|    null|              null|    BASE|
|root.dbtest.plant9.device84.m184| null|root.dbtest|   INT32|     RLE|     SNAPPY|null|      null|    null|              null|    BASE|
+--------------------------------+-----+-----------+--------+--------+-----------+----+----------+--------+------------------+--------+

• DESC: descending order
• ASC: ascending order (default if not specified)

Design & Implementation Details

1. Syntax Extension

• Updated the grammar of SHOW TIMESERIES to support orderByTimeseriesClause.
• Added ordering-related fields to ShowTimeSeriesStatement to record sorting requirements.

2. Logical Plan Construction

• Introduced a SortNode at the top of the logical plan to enable global ordering across partitions.
• For single-partition queries, LIMIT and OFFSET are pushed down to the metadata tree traversal stage in LogicalPlanVisitor.

3. Limit/Offset Handling in Multi-Partition Queries

• For multi-partition queries, OFFSET cannot be pushed down.
  Instead, limit' = limit + offset is used.
• Fixed a bug in the previous implementation:
  when limit = 0 (which is treated as unlimited in IoTDB), limit' was incorrectly pushed down, causing unexpected truncation of results.

4. Ordered Traversal in Metadata Tree

• In MTreeBelowSGMemoryImpl, the iteration strategy of child nodes in schemaReader is overridden under ordering mode.
• Child nodes are traversed in lexicographical order by name.

5. Subtree Measurement Count

• Implemented subtree measurement statistics (only for in-memory metadata tree):

  • Added subtreeMeasurementCount to IMemMNode and related classes.
  • Maintained subtreeMeasurementCount along ancestor paths during measurement insertion and deletion.
  • This value is not persisted; it is initialized via a DFS during metadata tree loading.

• During schemaReader construction, acceptFullMatchedNode is overridden to skip subtree traversal when subtreeMeasurementCount < offset.

Tests

Functional Tests

• Added IoTDBShowTimeseriesOrderByTimeseriesIT to verify correctness of ordering and offset behavior.

Performance Evaluation

• Evaluated performance on a single-partition dataset with a typical three-level hierarchy:

  root.plantA.deviceB.measurementC
  

  with approximately 900,000 measurements.
• Query pattern:

  SHOW TIMESERIES root.dbtest.** order by timeseries LIMIT 100 OFFSET X;

  where X ranges from 0 to 900,000 with a step of 5,000.
• Compared the original implementation and the optimized version.
• Results are shown in the figure below:

• Detailed benchmark methodology and results are available at: [link].

Impact

• Enables deterministic ordering for SHOW TIMESERIES.
• Significantly reduces traversal cost for large OFFSET values in single-partition scenarios $O(limit+offset)\to O(limit+TreeHeight)$.
• Improves correctness of limit/offset handling in multi-partition queries.
• Introduces minimal overhead to metadata maintenance (in-memory only).