Download sql_queries.py from vedsadani/Text2SQL: direct link, hf CLI and curl.
- Browser
- Download file 11.2 kB
-
https://huggingface.co/spaces/vedsadani/Text2SQL/resolve/eea36e79fbf7cd8b396ef9e880dacaf9852b9385/sql_queries.py
- Command line
-
hf download hf://spaces/vedsadani/Text2SQL@eea36e79fbf7cd8b396ef9e880dacaf9852b9385/sql_queries.py
-
curl -L -o sql_queries.py https://huggingface.co/spaces/vedsadani/Text2SQL/resolve/eea36e79fbf7cd8b396ef9e880dacaf9852b9385/sql_queries.py
11.2 kB
| # -*- coding: utf-8 -*- | |
| """SQL_Queries.ipynb | |
| Automatically generated by Colab. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1JMMq3yCv2xWTEZbs9S28qx4lXdF88M5d | |
| """ | |
| sql_queries = { | |
| 'Count the number of records in the dataset': 'SELECT COUNT(*) FROM ved_test.synthetic_data;', | |
| 'Get the average Weighted_Avg_PRB_Util_UL': 'SELECT AVG(Weighted_Avg_PRB_Util_UL) FROM ved_test.synthetic_data;', | |
| 'Get the minimum UE_Pwr_Restricted_Pct value': 'SELECT MIN(UE_Pwr_Restricted_Pct) FROM ved_test.synthetic_data;', | |
| 'Calculate the total UE_Pwr_Unrestricted_Pct_Num': 'SELECT SUM(UE_Pwr_Unrestricted_Pct_Num) FROM ved_test.synthetic_data;', | |
| 'Get the distinct values of Network_Engineer': 'SELECT DISTINCT Network_Engineer FROM ved_test.synthetic_data;', | |
| 'Count the number of records for each Network_Engineer': 'SELECT Network_Engineer, COUNT(*) FROM ved_test.synthetic_data GROUP BY Network_Engineer;', | |
| 'Calculate the average RTT for each Network_Engineer': 'SELECT Network_Engineer, AVG(RTT) AS avg_rtt FROM ved_test.synthetic_data GROUP BY Network_Engineer;', | |
| 'Calculate the average Jitter for weekends and weekdays': 'SELECT WEEKEND, AVG(Jitter) AS avg_jitter FROM ved_test.synthetic_data GROUP BY WEEKEND;', | |
| 'Get the average Jitter and Packet Loss for each hour': 'SELECT Hour, AVG(Jitter) AS avg_jitter, AVG(`DL Packet Loss Pct`) AS avg_packet_loss FROM ved_test.synthetic_data GROUP BY Hour ORDER BY Hour;', | |
| 'Find the top 5 records with the highest UPTP_Mbps': 'SELECT * FROM ved_test.synthetic_data ORDER BY UPTP_Mbps DESC LIMIT 5;', | |
| 'Calculate the average HARQ_BLER_Pct for each 5G_Reliability_Category': 'SELECT `5G Reliability Category`, AVG(HARQ_BLER_Pct) AS avg_harq_bler_pct FROM ved_test.synthetic_data GROUP BY `5G Reliability Category`;', | |
| 'Find the average RTT and Jitter for each combination of Market and Hour': 'SELECT Market, Hour, AVG(RTT) AS avg_rtt, AVG(Jitter) AS avg_jitter FROM ved_test.synthetic_data GROUP BY Market, Hour;', | |
| 'Get the top 3 Network_Engineers with the highest average 5G_Reliability_Score': 'SELECT Network_Engineer, AVG(`5G Reliability Score`) AS avg_reliability_score FROM ved_test.synthetic_data GROUP BY Network_Engineer ORDER BY avg_reliability_score DESC LIMIT 3;', | |
| 'Calculate the average Weighted_Avg_PRB_Util_UL and DL_MAC_Vol_Scell_Pct for each day of the week': 'SELECT EXTRACT(DAYOFWEEK FROM Timestamp) AS day_of_week, AVG(Weighted_Avg_PRB_Util_UL) AS avg_prb_util, AVG(`DL MAC Vol Scell Pct`) AS avg_dl_mac_vol FROM ved_test.synthetic_data GROUP BY day_of_week;', | |
| 'Get the average HARQ_BLER_Pct for each Market on weekends': 'SELECT Market, AVG(HARQ_BLER_Pct) AS avg_harq_bler_pct FROM ved_test.synthetic_data WHERE WEEKEND = 1 GROUP BY Market;', | |
| 'Calculate the total Bearer Releases for records where Bearer_Setup_Failure_Pct is greater than 80% and group by Market': 'SELECT Market, SUM(`Bearer Releases`) AS total_bearer_release FROM ved_test.synthetic_data WHERE Bearer_Setup_Failure_Pct > 0.8 GROUP BY Market;', | |
| 'Find the Market with the highest total UE_Pwr_Unrestricted_Pct_Num and the total value': 'SELECT Market, SUM(UE_Pwr_Unrestricted_Pct_Num) AS total_unrestricted_pwr FROM ved_test.synthetic_data GROUP BY Market ORDER BY total_unrestricted_pwr DESC LIMIT 1;', | |
| 'Get the average UPTP_Mbps and RRC_Reestab_Attempts for each Market for weekdays and weekends': 'SELECT Market, WEEKEND, AVG(UPTP_Mbps) AS avg_uptp_mbps, AVG(RRC_Reestab_Attempts) AS avg_rrc_attempts FROM ved_test.synthetic_data GROUP BY Market, WEEKEND;', | |
| 'Find the correlation between RTT and Jitter for each Market': 'SELECT Market, CORR(RTT, Jitter) AS rtt_jitter_correlation FROM ved_test.synthetic_data GROUP BY Market;', | |
| 'Calculate the average Weighted_Avg_PRB_Util_UL for each day of the week': 'SELECT EXTRACT(DAYOFWEEK FROM Timestamp) AS day_of_week, AVG(Weighted_Avg_PRB_Util_UL) AS avg_prb_util FROM ved_test.synthetic_data GROUP BY day_of_week;', | |
| 'Calculate the average UPTP_Mbps for each 5G_Reliability_Category during weekdays and weekends': 'SELECT `5G Reliability Category`, WEEKEND, AVG(UPTP_Mbps) AS avg_uptp_mbps FROM ved_test.synthetic_data GROUP BY `5G Reliability Category`, WEEKEND ORDER BY `5G Reliability Category`, WEEKEND;', | |
| 'Identify the hour with the highest average HARQ_BLER_Pct': 'SELECT Hour, AVG(HARQ_BLER_Pct) AS avg_harq_bler_pct FROM ved_test.synthetic_data GROUP BY Hour ORDER BY avg_harq_bler_pct DESC LIMIT 1;', | |
| 'Calculate the standard deviation of 5G_Reliability_Score for each Network_Engineer': 'SELECT Network_Engineer, STDDEV(`5G Reliability Score`) AS stddev_reliability_score FROM ved_test.synthetic_data GROUP BY Network_Engineer;', | |
| 'Find the top 3 hours with the highest total UE_Pwr_Unrestricted_Pct_Num during weekends': 'SELECT Hour, SUM(UE_Pwr_Unrestricted_Pct_Num) AS total_unrestricted_pwr FROM ved_test.synthetic_data WHERE WEEKEND = 1 GROUP BY Hour ORDER BY total_unrestricted_pwr DESC LIMIT 3;', | |
| 'Determine the Network_Engineer with the highest average DL MAC Vol Scell Pct and the average value': 'SELECT Network_Engineer, AVG(`DL MAC Vol Scell Pct`) AS avg_dl_mac_vol FROM ved_test.synthetic_data GROUP BY Network_Engineer ORDER BY avg_dl_mac_vol DESC LIMIT 1;', | |
| 'Find the variance in Jitter for each 5G_Reliability_Category': 'SELECT `5G Reliability Category`, VARIANCE(Jitter) AS variance_jitter FROM ved_test.synthetic_data GROUP BY `5G Reliability Category`;', | |
| 'Calculate the correlation between RTT and 5G Reliability Value for each Reliability Category': 'SELECT `5G Reliability Category`, CORR(RTT, `5G Reliability Value`) AS rtt_reliability_correlation FROM ved_test.synthetic_data GROUP BY `5G Reliability Category`;', | |
| 'Calculate the average and median MTTR for each Network Engineer filtered by 5G Reliability Value being above the overall average score': '''SELECT Network_Engineer, AVG(MTTR) AS avg_mttr, ( | |
| SELECT AVG(middle_vals) | |
| FROM ( | |
| SELECT MTTR AS middle_vals, ROW_NUMBER() OVER (PARTITION BY Network_Engineer ORDER BY MTTR) AS rnk, COUNT(*) OVER (PARTITION BY Network_Engineer) AS cnt | |
| FROM ved_test.synthetic_data | |
| WHERE `5G Reliability Value` > (SELECT AVG(`5G Reliability Value`) FROM ved_test.synthetic_data) | |
| ) AS subquery | |
| WHERE rnk IN (FLOOR((cnt + 1) / 2.0), FLOOR((cnt + 2) / 2.0)) | |
| ) AS median_mttr | |
| FROM ved_test.synthetic_data | |
| WHERE `5G Reliability Value` > (SELECT AVG(`5G Reliability Value`) FROM ved_test.synthetic_data) | |
| GROUP BY Network_Engineer;''', | |
| 'Find the count of records per 5G_Reliability_Category where 5G_Reliability_Value is below the average for the category': '''SELECT `5G Reliability Category`, COUNT(*) as count | |
| FROM ved_test.synthetic_data AS s1 | |
| WHERE `5G Reliability Value` < ( | |
| SELECT AVG(`5G Reliability Value`) | |
| FROM ved_test.synthetic_data AS s2 | |
| WHERE s2.`5G Reliability Category` = s1.`5G Reliability Category` | |
| ) | |
| GROUP BY `5G Reliability Category`;''', | |
| 'Find the top 5 records with the highest HO Attempts for each Network_Engineer': '''SELECT s1.* | |
| FROM ved_test.synthetic_data s1 | |
| JOIN ( | |
| SELECT Network_Engineer, `HO Attempts` | |
| FROM ( | |
| SELECT Network_Engineer, `HO Attempts`, ROW_NUMBER() OVER (PARTITION BY Network_Engineer ORDER BY `HO Attempts` DESC) AS rn | |
| FROM ved_test.synthetic_data | |
| ) temp | |
| WHERE rn <= 5 | |
| ) s2 | |
| ON s1.Network_Engineer = s2.Network_Engineer AND s1.`HO Attempts` = s2.`HO Attempts`;''', | |
| 'Calculate the exponential moving average of 5G_Reliability_Value for each Network_Engineer with a smoothing factor of 0.1': '''WITH ema AS ( | |
| SELECT Timestamp, Network_Engineer, `5G Reliability Value`, CAST(NULL AS FLOAT64) AS ema_value, | |
| ROW_NUMBER() OVER (PARTITION BY Network_Engineer ORDER BY Timestamp) AS row_num | |
| FROM ved_test.synthetic_data | |
| ) | |
| SELECT a.Timestamp, a.Network_Engineer, a.`5G Reliability Value`, | |
| CASE | |
| WHEN a.row_num = 1 THEN a.`5G Reliability Value` | |
| ELSE (0.1 * a.`5G Reliability Value` + 0.9 * b.ema_value) | |
| END AS ema_value | |
| FROM ema a | |
| LEFT JOIN | |
| ema b | |
| ON a.Network_Engineer = b.Network_Engineer AND a.row_num = b.row_num + 1;''', | |
| "Find the records with the highest HARQ_BLER_Pct for each 5G_Reliability_Category": '''SELECT s1.* | |
| FROM ved_test.synthetic_data s1 | |
| JOIN ( | |
| SELECT `5G Reliability Category`, MAX(HARQ_BLER_Pct) AS max_harq_bler_pct | |
| FROM ved_test.synthetic_data | |
| GROUP BY `5G Reliability Category` | |
| ) s2 | |
| ON s1.`5G Reliability Category` = s2.`5G Reliability Category` AND s1.HARQ_BLER_Pct = s2.max_harq_bler_pct;''', | |
| "Identify the top 3 hours with the highest average UPTP_Mbps for each Market, including the variance in Jitter during these hours": '''WITH avg_uptp AS ( | |
| SELECT Market, Hour, AVG(UPTP_Mbps) AS avg_uptp_mbps, VARIANCE(Jitter) AS jitter_variance, | |
| ROW_NUMBER() OVER (PARTITION BY Market ORDER BY AVG(UPTP_Mbps) DESC) AS rn | |
| FROM ved_test.synthetic_data | |
| GROUP BY Market, Hour | |
| ) | |
| SELECT Market, Hour, avg_uptp_mbps, jitter_variance | |
| FROM avg_uptp | |
| WHERE rn <= 3;''', | |
| "Determine the Sector with the highest variance in 5G Reliability Value and its corresponding average Context Drop Percent": '''WITH variance_scores AS ( | |
| SELECT Sector, VARIANCE(`5G Reliability Value`) AS score_variance, AVG(Context_Drop_Pct) AS avg_context_drop | |
| FROM ved_test.synthetic_data | |
| GROUP BY Sector | |
| ) | |
| SELECT Sector, score_variance, avg_context_drop | |
| FROM variance_scores | |
| ORDER BY score_variance DESC | |
| LIMIT 1;''', | |
| "Find hours where the average UPTP_Mbps is significantly different than the daily average (more than 2 standard deviations away from the mean)": '''WITH daily_stats AS ( | |
| SELECT DATE(Timestamp) AS day, AVG(UPTP_Mbps) AS daily_avg_uptp, STDDEV(UPTP_Mbps) AS daily_stddev_uptp | |
| FROM ved_test.synthetic_data | |
| GROUP BY day | |
| ), | |
| hourly_stats AS ( | |
| SELECT DATE(Timestamp) AS day, EXTRACT(HOUR FROM Timestamp) AS hour, AVG(UPTP_Mbps) AS hourly_avg_uptp | |
| FROM ved_test.synthetic_data | |
| GROUP BY day, hour | |
| ) | |
| SELECT | |
| hs.day, hs.hour, hs.hourly_avg_uptp, ds.daily_avg_uptp, ds.daily_stddev_uptp | |
| FROM hourly_stats hs | |
| JOIN daily_stats ds ON hs.day = ds.day | |
| WHERE hs.hourly_avg_uptp > (ds.daily_avg_uptp + 2 * ds.daily_stddev_uptp) | |
| OR hs.hourly_avg_uptp < (ds.daily_avg_uptp - 2 * ds.daily_stddev_uptp) | |
| ORDER BY hs.day, hs.hour;''', | |
| "Identify Days where more than 10% of the records have RRC Setup Failure above 25% for each region": '''WITH daily_rrc_failures AS ( | |
| SELECT | |
| Region, DATE(Timestamp) AS day, COUNT(*) AS total_records, | |
| SUM(CASE WHEN `RRC Setup Failure% 5G`> 0.25 THEN 1 ELSE 0 END) AS high_failure_count | |
| FROM ved_test.synthetic_data | |
| GROUP BY Region, day | |
| ), | |
| daily_rrc_failure_ratio AS ( | |
| SELECT | |
| Region, day, total_records, high_failure_count, (high_failure_count / total_records) * 100 AS failure_ratio | |
| FROM daily_rrc_failures | |
| ) | |
| SELECT | |
| Region, day, total_records, high_failure_count, failure_ratio | |
| FROM daily_rrc_failure_ratio | |
| WHERE failure_ratio > 10 | |
| ORDER BY Region, day;''' | |
| } |