120 lines
8.2 KiB
Markdown
120 lines
8.2 KiB
Markdown
# InterferenceETL
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InterferenceETL follows the newest interference KPI time group in Metrix storage. It reads seven ZIP/XLSX source types, converts each `Sheet0` to CSV, and creates one merged high-interference summary.
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Source file names are identified by one of the seven fixed prefixes plus a final `_YYYYMMDDHHMMHHMM.zip`; text between the prefix and time is unrestricted. Only the first `YYYYMMDDHHMM` start time is used for grouping. Start times are rounded down to natural 15-minute boundaries, so `12:00` through `12:14` belong to `12:00`. This also works unchanged when all providers switch together to hourly or daily delivery.
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Every run follows only the group containing the newest source start time. It never falls back or backfills an older group. If any source type is missing, the script prints `status=waiting` with the missing types and exits successfully. When one source has multiple files in the group, its latest start time wins.
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## Output
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Each run writes one window directory:
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```text
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output/20260731100000/
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├── converted/
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│ ├── 5G下FDD干扰监控_2026073110001100.csv
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│ ├── 5G干扰监控_2026073110001100.csv
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│ └── ... seven source CSV files
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├── interference_summary_20260731100000.csv
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└── manifest.json
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```
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For every processed group, the script also reads the latest filename-dated XLSX from each configured CellData directory. It builds CellData CGI as `460-00-{eNB/gNB}-{CI}` and adds coordinates plus direction angle to matching interference rows. Unmatched rows keep empty coordinates and use `0` for azimuth.
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The summary columns are:
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```text
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metric_time,network_type,cgi,cell_name,interference_dbm,prev_interference_dbm,longitude,latitude,azimuth,nearby_count,prev_nearby_count
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```
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All selected workbook rows must belong to the selected natural 15-minute group. Every summary row receives the same normalized `metric_time`; a row outside the group fails the run before database or history output.
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`network_type` is derived from the seven source types: both `5G...` sources are `2.6G`, both `700M...` sources are `700M`, and SDR/反开 sources are `4G`. The summary and database keep only high-interference rows: `2.6G >= -107 dBm` and `700M/4G >= -110 dBm`. Converted source CSV files remain full source conversions.
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`nearby_count` is the number of other high-interference cells from the same selected time group within 1 km, across all network types. The cell itself is excluded, the 1 km boundary is included, and rows without coordinates use `0`. Candidate cells are found through a 1 km spatial grid index and confirmed with exact Haversine distance.
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`prev_interference_dbm` and `prev_nearby_count` come from the previously retained database time, matched by CGI before the current batch replaces old rows. They represent the same cell's previous-period interference value and nearby high-interference count. On the first run, or when a CGI did not exist in the previous period, both fields are empty in CSV/history output and `NULL` in MySQL.
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The script never modifies or deletes source storage files. Before downloading source ZIP files or CellData, it compares the normalized target time with the database. A target already present, or older than the database, is not processed again.
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The database table contains normalized `metric_time DATETIME`, `network_type VARCHAR(16)`, `interference_dbm DECIMAL(10,3)`, nullable `prev_interference_dbm DECIMAL(10,3)`, nullable `longitude` and `latitude`, `azimuth DECIMAL(6,2) NOT NULL DEFAULT 0`, `nearby_count INT NOT NULL DEFAULT 0`, and nullable `prev_nearby_count INT`. A successful transaction replaces the target batch and deletes every other database time, so the table retains only the latest processed group. The previous-period values are read before this replacement transaction.
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After the database succeeds, the same eleven result columns are uploaded as GBK CSV to:
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```text
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/网优日常优化数据文档/(勿删)干扰定时小时指标/干扰历史数据/YYYY-MM-DD/干扰数据处理结果_YYYYMMDDHHMMSS.csv
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```
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The filename time comes from normalized `metric_time`, never the server clock. If the database already contains the target time but its history CSV is missing or empty, the script exports that time from the database and repairs the history file without reprocessing source data.
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Only the final history CSV uploaded to Metrix Storage uses GBK without a UTF-8 BOM. Source non-breaking spaces (`U+00A0`) are normalized to ordinary spaces in this history file because GBK cannot encode them; other unsupported characters still fail visibly. The seven local converted CSV files and local merged summary remain UTF-8 with BOM, and `manifest.json` remains UTF-8 JSON.
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CGI is generated with fixed rules:
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- NR (`5G干扰监控`, `700M干扰监控`): `{gNBplmn}-{gNBId}-{cellId}`.
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- 4G (the other five source types): `460-00-{eNodeBID}-{小区ID}`, using each source schema's actual equivalent column names.
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The Metrix API address, API Token, and database connection ID are constants in `runtime_config.py`; they are not project environment variables. Copy `runtime_config.example.py` to `runtime_config.py` and fill in the actual Token and the `conn_id` of `ShareMySQL`. The fixed database is `interference_etl`, the fixed table is `interference_hourly_summary`, and the script creates both automatically when they do not exist.
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The five CellData directories are fixed in `CELL_DATA_DIRECTORIES`. In each directory, only XLSX files ending with a valid `YYYYMMDD.xlsx` date are considered, and the latest date is selected. CellData column `方向角` maps to summary/database column `azimuth`; an empty source value becomes `0`.
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## Local development
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```powershell
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python -m pip install -r requirements.txt
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python -m unittest discover -s tests -v
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python main.py --source-dir C:\path\to\mock-or-exported-tree --output-dir output --no-database
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```
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Use `--window 2026073110001100` to select the natural 15-minute group containing that source start time. Without it, the newest observed source start time determines the group. Incomplete groups wait and never fall back.
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## Metrix Script Management
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The target server is offline. Build the dependency image locally, then generate a self-contained Script Management upload ZIP:
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```powershell
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docker build -t interference-etl-runtime:1.1 .
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python scripts\build_offline_package.py
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```
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The generated `dist/InterferenceETL-offline-1.1.zip` contains `main.py`, `runtime_config.py`, a ZIP execution entry point, and a `vendor/` directory containing `openpyxl` and `et_xmlfile`. The builder verifies imports and ZIP execution using the standard `python:3.13.11-slim` image, so the uploaded workspace does not need an online `pip install` or a custom runtime image. The build fails when `runtime_config.py` is missing.
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Create the project, then upload and extract the ZIP in its Script Management workspace. The normal file tree should contain `main.py` at `/workspace/main.py`. Use these project settings:
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```text
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Name: InterferenceETL
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Language: python
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Base image: python:3.13.11-slim
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Network: bridge
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Run command: python main.py
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Timeout: 1800 seconds
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```
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If the server keeps the ZIP as one file instead of extracting it, use `python InterferenceETL-offline-1.1.zip` as the run command. The ZIP contains `__main__.py` for this mode.
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Configure only run-specific source and output settings in the project environment:
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```json
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{
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"METRIX_STORAGE_ID": "stg_4d9a910d72",
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"INTERFERENCE_SOURCE_ROOT": "/网优日常优化数据文档/(勿删)干扰定时小时指标",
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"INTERFERENCE_OUTPUT_DIR": "/workspace/output",
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"INTERFERENCE_LOOKBACK_DAYS": "3"
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}
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```
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Both storage reads and database writes use the Metrix API at `http://188.5.127.115:18271`. SSH remains the deployment and operational channel for uploading files, starting runs, and reading logs.
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## CLI options
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```text
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--source-dir PATH Read a local directory tree instead of Metrix API
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--output-dir PATH Output root, default output or INTERFERENCE_OUTPUT_DIR
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--window WINDOW Select the natural 15-minute group for a 16-digit source window
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--lookback-days N Number of newest date directories scanned, default 3
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--storage-id ID Metrix storage connection ID
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--root PATH Source directory in Metrix storage
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--no-database Generate CSV files without writing the database
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```
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