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feat: 邻近高干扰小区数按制式拆分统计

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nixevol
2026-08-11 16:59:48 +08:00
parent eca4c5cbb1
commit 3835a0b928
4 changed files with 126 additions and 27 deletions
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README.md
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@@ -25,7 +25,7 @@ For every processed group, the script also reads the latest filename-dated XLSX
The summary columns are:
```text
metric_time,network_type,cgi,cell_name,interference_dbm,prev_interference_dbm,longitude,latitude,azimuth,nearby_count,prev_nearby_count
metric_time,network_type,cgi,cell_name,interference_dbm,prev_interference_dbm,longitude,latitude,azimuth,nearby_count,nearby_26g,nearby_700m,nearby_tdd,nearby_fdd,prev_nearby_count,prev_nearby_26g,prev_nearby_700m,prev_nearby_tdd,prev_nearby_fdd
```
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.
@@ -34,15 +34,17 @@ All selected workbook rows must belong to the selected natural 15-minute group.
`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.
`nearby_26g`, `nearby_700m`, `nearby_tdd`, and `nearby_fdd` split the same neighbors by the neighbor's `network_type`. Each field defaults to `0`, and the four values always add up to `nearby_count`.
When multiple retained source rows have the same CGI, the summary keeps the row with the numerically largest interference value. Equal values keep the first row encountered. Deduplication happens before nearby-cell counting and database insertion; converted source CSVs remain complete.
`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.
`prev_interference_dbm`, `prev_nearby_count`, and the four `prev_nearby_26g/700m/tdd/fdd` fields 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 counts. On the first run, or when a CGI did not exist in the previous period, these fields are empty in CSV/history output and `NULL` in MySQL.
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.
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.
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`, the five `NOT NULL DEFAULT 0` INT count columns (`nearby_count`, `nearby_26g`, `nearby_700m`, `nearby_tdd`, `nearby_fdd`), and the five nullable INT previous-period count columns (`prev_nearby_count`, `prev_nearby_26g`, `prev_nearby_700m`, `prev_nearby_tdd`, `prev_nearby_fdd`). 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.
After the database succeeds, the same eleven result columns are uploaded as GBK CSV to:
After the database succeeds, the same nineteen result columns are uploaded as GBK CSV to:
```text
/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