package main

import (
	"context"
	"github.com/aws/aws-sdk-go-v2/config"
	"github.com/aws/aws-sdk-go-v2/service/timestreamquery"
	"go_sample/utils"
	"net/http"
	"os"

	"flag"
	"fmt"
)

func ExecuteSampleQueries(queryClient *timestreamquery.Client, databaseName string, tableName string, f *os.File) {
	HOSTNAME := "host-24Gju"
	QUERY_LIMIT := 200
	MAX_ROWS := int32(200)

	// 1. Find the average, p90, p95, and p99 CPU utilization for a specific EC2 host over the past 2 hours.
	QUERY_1 := fmt.Sprintf("SELECT region, az, hostname, BIN(time, 15s) AS binned_timestamp,"+
		"ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization,"+
		"ROUND(APPROX_PERCENTILE(cpu_utilization, 0.9), 2) AS p90_cpu_utilization,"+
		"ROUND(APPROX_PERCENTILE(cpu_utilization, 0.95), 2) AS p95_cpu_utilization,"+
		"ROUND(APPROX_PERCENTILE(cpu_utilization, 0.99), 2) AS p99_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE measure_name = 'metrics' AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY region, hostname, az, BIN(time, 15s) "+
		"ORDER BY binned_timestamp ASC", databaseName, tableName, HOSTNAME)

	//2. Identify EC2 hosts with CPU utilization that is higher by 10%  or more compared to the average CPU utilization of the entire fleet for the past 2 hours.
	QUERY_2 := fmt.Sprintf("WITH avg_fleet_utilization AS ( "+
		"SELECT COUNT(DISTINCT hostname) AS total_host_count, AVG(cpu_utilization) AS fleet_avg_cpu_utilization "+
		"FROM %s.%s WHERE measure_name = 'metrics' "+
		"AND time > ago(2h)), avg_per_host_cpu AS ( "+
		"SELECT region, az, hostname, AVG(cpu_utilization) AS avg_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE measure_name = 'metrics' "+
		"AND time > ago(2h) "+
		"GROUP BY region, az, hostname) "+
		"SELECT region, az, hostname, avg_cpu_utilization, fleet_avg_cpu_utilization "+
		"FROM avg_fleet_utilization, avg_per_host_cpu "+
		"WHERE avg_cpu_utilization > 1.1 * fleet_avg_cpu_utilization "+
		"ORDER BY avg_cpu_utilization DESC", databaseName, tableName, databaseName, tableName)

	//3. Find the average CPU utilization binned at 30 second intervals for a specific EC2 host over the past 2 hours.
	QUERY_3 := fmt.Sprintf("SELECT BIN(time, 30s) AS binned_timestamp, ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization, "+
		"hostname FROM %s.%s "+
		"WHERE measure_name = 'metrics' "+
		"AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY hostname, BIN(time, 30s) "+
		"ORDER BY binned_timestamp ASC", databaseName, tableName, HOSTNAME)

	//4. Find the average CPU utilization binned at 30 second intervals for a specific EC2 host over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_4 := fmt.Sprintf("WITH binned_timeseries AS ("+
		"SELECT hostname, BIN(time, 30s) AS binned_timestamp, ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization "+
		"FROM %s.%s WHERE measure_name = 'metrics' "+
		"AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY hostname, BIN(time, 30s)), interpolated_timeseries AS ( "+
		"SELECT hostname, INTERPOLATE_LINEAR( "+
		"CREATE_TIME_SERIES(binned_timestamp, avg_cpu_utilization), "+
		"SEQUENCE(min(binned_timestamp), max(binned_timestamp), 15s)) AS interpolated_avg_cpu_utilization "+
		"FROM binned_timeseries "+
		"GROUP BY hostname) "+
		"SELECT time, ROUND(value, 2) AS interpolated_cpu "+
		"FROM interpolated_timeseries "+
		"CROSS JOIN UNNEST(interpolated_avg_cpu_utilization)", databaseName, tableName, HOSTNAME)

	//5. Find the average CPU utilization binned at 30 second intervals for a specific EC2 host over the past 2 hours, filling in the missing values using interpolation based on the last observation carried forward.
	QUERY_5 := fmt.Sprintf("WITH binned_timeseries AS ( "+
		"SELECT hostname, BIN(time, 30s) AS binned_timestamp, ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization "+
		"FROM %s.%s WHERE measure_name = 'metrics' AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY hostname, BIN(time, 30s)), interpolated_timeseries AS ("+
		"SELECT hostname, INTERPOLATE_LOCF(CREATE_TIME_SERIES(binned_timestamp, avg_cpu_utilization), "+
		"SEQUENCE(min(binned_timestamp), max(binned_timestamp), 15s)) AS interpolated_avg_cpu_utilization "+
		"FROM binned_timeseries "+
		"GROUP BY hostname) "+
		"SELECT time, ROUND(value, 2) AS interpolated_cpu FROM interpolated_timeseries "+
		"CROSS JOIN UNNEST(interpolated_avg_cpu_utilization)", databaseName, tableName, HOSTNAME)

	//6. Find the average CPU utilization binned at 30 second intervals for a specific EC2 host over the past 2 hours, filling in the missing values using interpolation based on a constant value.
	QUERY_6 := fmt.Sprintf("WITH binned_timeseries AS ( "+
		"SELECT hostname, BIN(time, 30s) AS binned_timestamp, ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE measure_name = 'metrics' "+
		"AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY hostname, BIN(time, 30s)), interpolated_timeseries AS ( "+
		"SELECT hostname, "+
		"INTERPOLATE_FILL(CREATE_TIME_SERIES(binned_timestamp, avg_cpu_utilization), "+
		"SEQUENCE(min(binned_timestamp), max(binned_timestamp), 15s), 10.0) AS interpolated_avg_cpu_utilization "+
		"FROM binned_timeseries "+
		"GROUP BY hostname) "+
		"SELECT time, ROUND(value, 2) AS interpolated_cpu "+
		"FROM interpolated_timeseries "+
		"CROSS JOIN UNNEST(interpolated_avg_cpu_utilization)", databaseName, tableName, HOSTNAME)

	//7. Find the average CPU utilization binned at 30 second intervals for a specific EC2 host over the past 2 hours, filling in the missing values using cubic spline interpolation.
	QUERY_7 := fmt.Sprintf("WITH binned_timeseries AS ("+
		"SELECT hostname, BIN(time, 30s) AS binned_timestamp, ROUND(AVG(cpu_utilization), 2) AS avg_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE measure_name = 'metrics' AND hostname = '%s' AND time > ago(2h) "+
		"GROUP BY hostname, BIN(time, 30s)), interpolated_timeseries AS ("+
		"SELECT hostname, INTERPOLATE_SPLINE_CUBIC("+
		"CREATE_TIME_SERIES(binned_timestamp, avg_cpu_utilization), "+
		"SEQUENCE(min(binned_timestamp), max(binned_timestamp), 15s)) AS interpolated_avg_cpu_utilization "+
		"FROM binned_timeseries "+
		"GROUP BY hostname) "+
		"SELECT time, ROUND(value, 2) AS interpolated_cpu "+
		"FROM interpolated_timeseries CROSS JOIN UNNEST(interpolated_avg_cpu_utilization)", databaseName, tableName, HOSTNAME)

	//8. Find the average CPU utilization binned at 30 second intervals for all EC2 hosts over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_8 := fmt.Sprintf("WITH per_host_min_max_timestamp AS ("+
		"SELECT hostname, min(time) as min_timestamp, max(time) as max_timestamp "+
		"FROM %s.%s "+
		"WHERE measure_name = 'metrics' AND time > ago(2h) "+
		"GROUP BY hostname), interpolated_timeseries AS ("+
		"SELECT m.hostname,"+
		"INTERPOLATE_LOCF("+
		"CREATE_TIME_SERIES(time, cpu_utilization), "+
		"SEQUENCE(MIN(ph.min_timestamp), MAX(ph.max_timestamp), 30s)) as interpolated_avg_cpu_utilization "+
		"FROM %s.%s m "+
		"INNER JOIN per_host_min_max_timestamp ph ON m.hostname = ph.hostname "+
		"WHERE measure_name = 'metrics' AND time > ago(2h)"+
		"GROUP BY m.hostname) "+
		"SELECT hostname, AVG(cpu_utilization) AS avg_cpu_utilization "+
		"FROM interpolated_timeseries "+
		"CROSS JOIN UNNEST(interpolated_avg_cpu_utilization) AS t (time, cpu_utilization) "+
		"GROUP BY hostname "+
		"ORDER BY avg_cpu_utilization DESC", databaseName, tableName, databaseName, tableName)

	//9. Find the percentage of measurements with CPU utilization above 70% for a specific EC2 host over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_9 := fmt.Sprintf("WITH time_series_view AS ("+
		"SELECT INTERPOLATE_LINEAR("+
		"CREATE_TIME_SERIES(time, ROUND(cpu_utilization,2)), "+
		"SEQUENCE(min(time), max(time), 10s)) AS interpolated_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE hostname = '%s' AND measure_name = 'metrics' AND time > ago(2h) "+
		"GROUP BY hostname) "+
		"SELECT FILTER(interpolated_cpu_utilization, x -> x.value > 70.0) AS cpu_above_threshold, "+
		"REDUCE(FILTER(interpolated_cpu_utilization, x -> x.value > 70.0), 0, (s, x) -> s + 1, s -> s) AS count_cpu_above_threshold, "+
		"ROUND(REDUCE(interpolated_cpu_utilization, CAST(ROW(0, 0) AS ROW(count_high BIGINT, count_total BIGINT)), "+
		"(s, x) -> CAST(ROW(s.count_high + IF(x.value > 70.0, 1, 0), s.count_total + 1) AS ROW(count_high BIGINT, count_total BIGINT)), "+
		"s -> IF(s.count_total = 0, NULL, CAST(s.count_high AS DOUBLE) / s.count_total)), 4) AS fraction_cpu_above_threshold "+
		"FROM time_series_view", databaseName, tableName, HOSTNAME)

	//10. List the measurements with CPU utilization lower than 75% for a specific EC2 host over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_10 := fmt.Sprintf("WITH time_series_view AS ("+
		"SELECT min(time) AS oldest_time, INTERPOLATE_LINEAR("+
		"CREATE_TIME_SERIES(time, ROUND(cpu_utilization, 2)),"+
		"SEQUENCE(min(time), max(time), 10s)) AS interpolated_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE hostname = '%s' AND measure_name = 'metrics' AND time > ago(2h) "+
		"GROUP BY hostname) "+
		"SELECT FILTER(interpolated_cpu_utilization, x -> x.value < 75 AND x.time > oldest_time + 1m) "+
		"FROM time_series_view", databaseName, tableName, HOSTNAME)

	//11. Find the total number of measurements with of CPU utilization of 0% for a specific EC2 host over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_11 := fmt.Sprintf("WITH time_series_view AS ("+
		"SELECT INTERPOLATE_LINEAR("+
		"CREATE_TIME_SERIES(time, ROUND(cpu_utilization, 2)), "+
		"SEQUENCE(min(time), max(time), 10s)) AS interpolated_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE hostname = '%s' AND measure_name = 'metrics' AND time > ago(2h) "+
		"GROUP BY hostname "+
		")"+
		"SELECT REDUCE(interpolated_cpu_utilization, "+
		"DOUBLE '0.0', "+
		"(s, x) -> s + 1, "+
		"s -> s) AS count_cpu "+
		"FROM time_series_view", databaseName, tableName, HOSTNAME)

	//12. Find the average CPU utilization for a specific EC2 host over the past 2 hours, filling in the missing values using linear interpolation.
	QUERY_12 := fmt.Sprintf("WITH time_series_view AS ("+
		"SELECT INTERPOLATE_LINEAR(CREATE_TIME_SERIES(time, ROUND(cpu_utilization, 2)), "+
		"SEQUENCE(min(time), max(time), 10s)) AS interpolated_cpu_utilization "+
		"FROM %s.%s "+
		"WHERE hostname = '%s' AND measure_name = 'metrics' AND time > ago(2h) "+
		"GROUP BY hostname) "+
		"SELECT REDUCE(interpolated_cpu_utilization, "+
		"CAST(ROW(0.0, 0) AS ROW(sum DOUBLE, count INTEGER)), "+
		"(s, x) -> CAST(ROW(x.value + s.sum, s.count + 1) AS ROW(sum DOUBLE, count INTEGER)), "+
		"s -> IF(s.count = 0, NULL, s.sum / s.count)) AS avg_cpu "+
		"FROM time_series_view", databaseName, tableName, HOSTNAME)

	//13. Running a query with multiple pages
	QUERY_13 := fmt.Sprintf("SELECT * FROM %s.%s LIMIT %d", databaseName, tableName,
		QUERY_LIMIT)

	queries := []string{QUERY_1, QUERY_2, QUERY_3, QUERY_4, QUERY_5, QUERY_6,
		QUERY_7, QUERY_8, QUERY_9, QUERY_10, QUERY_11, QUERY_12, QUERY_13}

	for index, query := range queries {
		msg := fmt.Sprintf("Running Query_%d : %s\n", index+1, query)
		fmt.Print(msg)
		utils.Write(f, msg)
		utils.RunQuery(&query, queryClient, f, MAX_ROWS)
		msg = "--------------------------------------------\n"
		utils.Write(f, msg)
		fmt.Print(msg)
	}
}

func main() {
	// process command line arguments
	region := flag.String("region", utils.REGION, "region")
	filePtr := flag.String("outputfile", "query_results.log", "output results file in the current folder")
	flag.Parse()

	// setup the query client
	tr := utils.LoadHttpSettings()
	cfg, err := config.LoadDefaultConfig(context.TODO(), config.WithRegion("us-east-1"))
	cfg.Region = *region
	cfg.HTTPClient = &http.Client{Transport: tr}

	utils.HandleError(err, "Failed to load config ", true)

	querySvc := timestreamquery.NewFromConfig(cfg)

	var f *os.File
	if *filePtr != "" {
		var ferr error
		f, ferr = os.Create(*filePtr)
		utils.Check(ferr)
		defer f.Close()
	}

	ExecuteSampleQueries(querySvc, utils.DATABASE_NAME,
		utils.TABLE_NAME, f)
}
