35 lines
2.4 KiB
Markdown
35 lines
2.4 KiB
Markdown
## MODIFIED Requirements
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### Requirement: Hold dataset cache SHALL execute a single Oracle query and cache the result
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The hold_dataset_cache module SHALL query Oracle once for the full hold/release fact set and cache it for subsequent derivations. For date ranges exceeding 60 days, the query SHALL be decomposed into monthly chunks via `BatchQueryOrchestrator`.
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#### Scenario: Primary query execution and caching
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- **WHEN** `execute_primary_query()` is called with date range and hold_type parameters
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- **THEN** a deterministic `query_id` SHALL be computed from the primary params (start_date, end_date) using SHA256
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- **THEN** if a cached DataFrame exists for this query_id (L1 or L2), it SHALL be used without querying Oracle
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- **THEN** if no cache exists, a single Oracle query SHALL fetch all hold/release records from `DW_MES_HOLDRELEASEHISTORY` for the date range (all hold_types)
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- **THEN** the result DataFrame SHALL be stored in both L1 (ProcessLevelCache) and L2 (Redis as parquet/base64)
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- **THEN** the response SHALL include `query_id`, trend, reason_pareto, duration, and list page 1
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#### Scenario: Long date range triggers batch decomposition
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- **WHEN** the date range exceeds 60 days (configurable via `BATCH_QUERY_TIME_THRESHOLD_DAYS`)
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- **THEN** the query SHALL be decomposed into ~31-day monthly chunks via `BatchQueryOrchestrator.decompose_by_time_range()`
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- **THEN** each chunk SHALL execute independently via `read_sql_df_slow` with the chunk's date sub-range
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- **THEN** chunk results SHALL be stored individually in Redis and merged via `pd.concat`
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- **THEN** the merged DataFrame SHALL be stored in the existing L1+L2 cache under the original query_id
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#### Scenario: Short date range uses direct query
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- **WHEN** the date range is 60 days or fewer
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- **THEN** the existing single-query path SHALL be used without batch decomposition
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#### Scenario: Cache TTL and eviction
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- **WHEN** a DataFrame is cached
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- **THEN** the cache TTL SHALL be 900 seconds (15 minutes)
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- **THEN** L1 cache max_size SHALL be 8 entries with LRU eviction
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- **THEN** the Redis namespace SHALL be `hold_dataset`
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#### Scenario: Redis parquet helpers use shared module
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- **WHEN** DataFrames are stored or loaded from Redis
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- **THEN** the module SHALL use `redis_df_store.redis_store_df()` and `redis_df_store.redis_load_df()` from the shared `core/redis_df_store.py` module
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- **THEN** inline `_redis_store_df` / `_redis_load_df` functions SHALL be removed
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