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aakash-project-422813-1230ad3ba9f1.json

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+{
+  "type": "service_account",
+  "project_id": "aakash-project-422813",
+  "private_key_id": "1230ad3ba9f12dec9a1ad4178690345e40e0ba18",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\ncNPrv2fsUQds2F4YsgGEq4E=\n-----END PRIVATE KEY-----\n",
+  "client_email": "big-query-account@aakash-project-422813.iam.gserviceaccount.com",
+  "client_id": "109047674488400696874",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/big-query-account%40aakash-project-422813.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
+}

sql_queries.py

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+# -*- 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;'''
+
+}