How to query tables to get cost of call - sql

What Query would I need to do to calculate cost of calls in mysql database?
Ive got two tables, one is a call log with call duration, and the other table is the tariff table with peak and offpeak rates, peaktime is 08:00:00 - 19:00:00 offpeak time is 19:00:00 - 08:00:00. rates for peak are say 10p a minute or 0.9992 a second or something on the lines of that. and offpeak 2p minute.
I want to know how to query the two tables to calculate the cost of call according to the call duration and the cost of the call - Rate per sec/minute.
Output would be on another table with CallerId, Source, Destination, call duration , cost of call

This seems relatively straight forward (which usually means I am missing something).
Starting with assumptions. Say the CALL_LOG table looks like this:
CallerId
Source
Destination
Duration
CallStartTime
CallStopTime
. . . and the TARRIFF table looks like this:
Id
RateType (Peak or OffPeak)
RateStartTime
RateStopTime
Rate
And let's assume you are using Oracle, since I don't see that specifically mentioned. But you say CDRs, so probably lots of records, so maybe Oracle. (NOTE: I removed the Oracle specific code and decided to do this as an inner join. Might be too slow though, depending on volume.)
And let's assume that the definition of an "off peak call" is a call that starts during an off-peak time, regardless of when it ends. (Note that this definition is critical to doing it correctly.)
Lastly, let's assume that there are only two rates, peak and off-peak, based on your comments. That seems strange, but ok. I would have thought that the times would differ by day, to allow for weekend rates, but you should be able to extrapolate.
So the cost for a call would then be
SELECT l.CallerId,
l.Source,
l.Destination,
l.Duration,
t.RateType,
l.Duration * t.Rate as Cost
FROM CALL_LOG l
INNER JOIN TARRIF t
ON l.CallStartTime BETWEEN t.RateStartTime and t.RateStopTime

Related

Amount of overlaps per minute

I would like to make an SQL-Statement in order to find the amount of users that are using a channel by date and time. Let me give you an example:
Let's call this table Data:
Date Start End
01.01.2020 17:00 17:30
01.01.2020 17:01 17:03
01.01.2020 17:29 18:30
Data is a table that shows when an user started the connection on a channel and the time the connection was closed. A connection can be made any time, which means from 00:00 until the next day.
What I am trying to achieve is to count the maximum number of connections that were made over a big period if time. Let's say 1st February to 1st April.
My idea was to make another table with timestamps in Excel. The table would display a Timestamp for every Minute in a specific date.
Then I tried to make a statement like:
SELECT *
FROM Data,Timestamps
WHERE Timestamps.Time BETWEEN Data.Start AND Data.End.
Now logically this statement does what is supposed to do. The only problem is that it is not really performant and therefore not finishing. With the amount of timestamps and the amount of data I have to check it is not able to finish.
Could anybody help me with this problem? Any other ideas I can try or how to improve my statement?
Regards!
So why dou you create another table in Excel and not directly in MS Access and then why won't you set up the indexes of the timestamps right. That will speed it up by factors.
By the way I think that your statement will print repeat every user that happened to match your Start .. End period, so the amount of rows produced will be enormous. You shall rather try
SELECT Timestamps.Time, COUNT(*)
FROM Data,Timestamps
WHERE Timestamps.Time BETWEEN Data.Start AND Data.End
GROUP BY Timestamps.Time;
But sorry if the syntax in MS Access is different.

Time gap calculation in MS Access

I have a table (Access 2016) tbl_b with date/time registrations
b_customer (num)
b_date (date)
b_start (date/time)
b_end (date/time)
I want to make a chart of all time registrations per day in a selected month and the gaps between those times. For this I need a query or table showing all times as source for the chart. I’m a bit lost how to approach this.
I assume the chart source needs consecutive records with all date and time registrations to do this. My approach would be create a temporary table (tmp) calculating all time periods where the customer is null. The next step would be a union query to combine the tbl_b and tmp table.
The tbl_b does not have records for every day, so I use a query generating all days in the selected month which shall be used in the chart (found this solution here: [Create a List of Dates in Access Query)
The disadvantage of using a tmp table for the “time gaps” is that it is not updating real time, where a query would provide this opportunity. I have about 20 queries to perform the end result, but MS Access keeps giving (expected) errors that the queries are too difficult.
Every query looks for difference between the in the previous query found end time and the next start time. On the other hand this approach has a weaknes as well, I thought 15 steps would be enough (no more than 15 gaps expected), but this is not sure.
Can anyone give me a head start how this can be accomplished by an easier (and actual working) method? Maybe VBA?
Thx!
Art

SQL for Next/Prior Business Day from Calendar table (in MS Access)

I have a Calendar table pulled from our mainframe DBs and saved as a local Access table. The table has history back to the 1930s (and I know we use back to the 50s in at least one place), resulting in 31k records. This Calendar table has 3 fields of interest:
Bus_Dt - every day, not just business days. Primary Key
Bus_Day_Ind - indicates if the day was a valid business day for the stock market.
Prir_Bus_Dt - the prior business day. Contains some errors (about 50), all old.
I have written a query to retrieve the first business day on or after the current calendar day, but it runs supremely slowly. (5+ minutes) I have examined the showplan output and see it is being run via an x-join, which between 30k+ record tables gives a solution space (and date comparisons) in the order of nearly 10 million. However, the actual task is not hard, and could be preformed comfortably by excel in minimal time using a simple sort.
My question is thus, is there any way to fix the poor performance of the query, or is this an inherent failing of SQL? (DB2 run on the mainframe also is slow, though not crushingly so. Throwing cycles at the problem and all that.) Secondarily, if I were to trust prir_bus_dt, can I get there better? Or restrict the date range (aka, "cheat"), or any other tricks I didn't think of yet?
SQL:
SELECT TE2Clndr.BUS_DT AS Cal_Dt
, Min(TE2Clndr_1.BUS_DT) AS Next_Bus_Dt
FROM TE2Clndr
, TE2Clndr AS TE2Clndr_1
WHERE TE2Clndr_1.BUS_DAY_IND="Y" AND
TE2Clndr.BUS_DT<=[te2clndr_1].[bus_dt]
GROUP BY TE2Clndr.BUS_DT;
Showplan:
Inputs to Query
Table 'TE2Clndr'
Table 'TE2Clndr'
End inputs to Query
01) Restrict rows of table TE2Clndr
by scanning
testing expression "TE2Clndr_1.BUS_DAY_IND="Y""
store result in temporary table
02) Inner Join table 'TE2Clndr' to result of '01)'
using X-Prod join
then test expression "TE2Clndr.BUS_DT<=[te2clndr_1].[bus_dt]"
03) Group result of '02)'
Again, the question is, can this be made better (faster), or is this already as good as it gets?
I have a new query that is much faster for the same job, but it depends on the prir_bus_dt field (which has some errors). It also isn't great theory since prior business day is not necessarily available on everyone's calendar. So I don't consider this "the" answer, merely an answer.
New query:
SELECT TE2Clndr.BUS_DT as Cal_Dt
, Max(TE2Clndr_1.BUS_DT) AS Next_Bus_Dt
FROM TE2Clndr
INNER JOIN TE2Clndr AS TE2Clndr_1
ON TE2Clndr.PRIR_BUS_DT = TE2Clndr_1.PRIR_BUS_DT
GROUP BY TE2Clndr.BUS_DT;
What about this approach
select min(bus_dt)
from te2Clndr
where bus_dt >= date()
and bus_day_ind = 'Y'
This is my reference for date() representing the current date

SQL to group time intervals by arbitrary time period

I need help with this SQL query. I have a big table with the following schema:
time_start (timestamp) - start time of the measurement,
duration (double) - duration of the measurement in seconds,
count_event1 (int) - number of measured events of type 1,
count_event2 (int) - number of measured events of type 2
I am guaranteed that the no rows will overlap - in SQL talk, there are no two rows such that time_start1 < time_start2 AND time_start1 + duration1 > time_start2.
I would like to design an efficient SQL query which would group the measurements by some arbitrary time period (I call it the group_period), for instance 3 hours. I have already tried something like this:
SELECT
ROUND(time_start/group_period,0) AS time_period,
SUM(count_event1) AS sum_event1,
SUM(count_event2) AS sum_event2
FROM measurements
GROUP BY time_period;
However, there seems to be a problem. If there is a measurement with duration greater than the group_period, I would expect such measurement to be grouped into all time period it belongs to, but since the duration is never taken into account, it gets grouped only into the first one. Is there a way to fix this?
Performance is of concern to me because in time, I expect the table size to grow considerably reaching millions, possibly tens or hundreds of millions of rows. Do you have any suggestions for indexes or any other optimizations to improve the speed of this query?
Based on Timekiller's advice, I have come up with the following query:
-- Since there's a problem with declaring variables in PostgreSQL,
-- we will be using aliases for the arguments required by the script.
-- First some configuration:
-- group_period = 3600 -- group by 1 hour (= 3600 seconds)
-- min_time = 1440226301 -- Sat, 22 Aug 2015 06:51:41 GMT
-- max_time = 1450926301 -- Thu, 24 Dec 2015 03:05:01 GMT
-- Calculate the number of started periods in the given interval in advance.
-- period_count = CEIL((max_time - min_time) / group_period)
SET TIME ZONE UTC;
BEGIN TRANSACTION;
-- Create a temporary table and fill it with all time periods.
CREATE TEMP TABLE periods (period_start TIMESTAMP)
ON COMMIT DROP;
INSERT INTO periods (period_start)
SELECT to_timestamp(min_time + group_period * coefficient)
FROM generate_series(0, period_count) as coefficient;
-- Group data by the time periods.
-- Note that we don't require exact overlap of intervals:
-- A. [period_start, period_start + group_period]
-- B. [time_start, time_start + duration]
-- This would yield the best possible result but it would also slow
-- down the query significantly because of the part B.
-- We require only: period_start <= time_start <= period_start + group_period
SELECT
period_start,
COUNT(measurements.*) AS count_measurements,
SUM(count_event1) AS sum_event1,
SUM(count_event2) AS sum_event2
FROM periods
LEFT JOIN measurements
ON time_start BETWEEN period_start AND (period_start + group_period)
GROUP BY period_start;
COMMIT TRANSACTION;
It does exactly what I was going for, so mission accomplished. However, I would still appreciate if anybody could give me some feedback to the performance of this query for the following conditions:
I expect the measurements table to have about 500-800 million rows.
The time_start column is primary key and has unique btree index on it.
I have no guarantees about min_time and max_time. I only know that group period will be chosen so that 500 <= period_count <= 2000.
(This turned out way too large for a comment, so I'll post it as an answer instead).
Adding to my comment on your answer, you probably should go with getting best results first and optimize later if it turns out to be slow.
As for performance, one thing I've learned while working with databases is that you can't really predict performance. Query optimizers in advanced DBMS are complex and tend to behave differently on small and large data sets. You'll have to get your table filled with some large sample data, experiment with indexes and read the results of EXPLAIN, there's no other way.
There are a few things to suggest, though I know Oracle optimizer much better than Postgres, so some of them might not work.
Things will be faster if all fields you're checking against are included in the index. Since you're performing a left join and periods is a base, there's probably no reason to index it, since it'll be included fully either way. duration should be included in the index though, if you're going to go with proper interval overlap - this way, Postgres won't have to fetch the row to calculate the join condition, index will suffice. Chances are it will not even fetch the table rows at all since it needs no other data than what exists in indexes. I think it'll perform better if it's included as the second field to time_start index, at least in Oracle it would, but IIRC Postgres is able to join indexes together, so perhaps a second index would perform better - you'll have to check it with EXPLAIN.
Indexes and math don't mix well. Even if duration is included in the index, there's no guarantee it will be used in (time_start + duration) - though, again, look at EXPLAIN first. If it's not used, try to either create a function-based index (that is, include time_start + duration as a field), or alter the structure of the table a bit, so that time_start + duration is a separate column, and index that column instead.
If you don't really need left join (that is, you're fine with missing empty periods), then use inner join instead - optimizer will likely start with a larger table (measurements) and join periods against it, possibly using hash join instead of nested loops. If you do that, than you should also index your periods table in the same fashion, and perhaps restructure it the same way, so that it contains start and end periods explicitly, as optimizer has even more options when it doesn't have to perform any operations on the columns.
Perhaps the most important, if you have max_time and min_time, USE IT to limit the results of measurements before joining! The smaller your sets, the faster it will work.

Simultaneous calls from CDR

I need to come up with an analysis of simultaneus events, when having only starttime and duration of each event.
Details
I've a standard CDR call detail record, that contains among others:
calldate (timedate of each call start
duration (int, seconds of call duration)
channel (a string)
What I need to come up with is some sort of analysys of simultaneus calls on each second, for a given timedate period. For example, a graph of simultaneous calls we had yesterday.
(The problem is the same if we have visitors logs with duration on a website and wish to obtain simultaneous clients for a group of web-pages)
What would your algoritm be?
I can iterate over records in the given period, and fill an array, where each bucket of the array corresponds to 1 second in the overall period. This works and seems to be fast, but if the timeperiod is big (say..1 year), I would need lots of memory (3600x24x365x4 bytes ~ 120MB aprox).
This is for a web-based, interactive app, so my memory footprint should be small enough.
Edit
By simultaneous, I mean all calls on a given second. Second would be my minimum unit. I cannot use something bigger (hour for example) becuse all calls during an hour do not need to be held at the same time.
I would implement this on the database. Using a GROUP BY clause with DATEPART, you could get a list of simultaneous calls for whatever time period you wanted, by second, minute, hour, whatever.
On the web side, you would only have to display the histogram that is returned by the query.
#eric-z-beard: I would really like to be able to implement this on the database. I like your proposal, and while it seems to lead to something, I dont quite fully understand it. Could you elaborate? Please recall that each call will span over several seconds, and each second need to count. If using DATEPART (or something like it on MySQL), what second should be used for the GROUP BY. See note on simultaneus.
Elaborating over this, I found a way to solve it using a temporary table. Assuming temp holds all seconds from tStart to tEnd, I could do
SELECT temp.second, count(call.id)
FROM call, temp
WHERE temp.second between (call.start and call.start + call.duration)
GROUP BY temp.second
Then, as suggested, the web app should use this as a histogram.
You can use a static Numbers table for lots of SQL tricks like this. The Numbers table simply contains integers from 0 to n for n like 10000.
Then your temp table never needs to be created, and instead is a subquery like:
SELECT StartTime + Numbers.Number AS Second
FROM Numbers
You can create table 'simultaneous_calls' with 3 fields: yyyymmdd Char(8),
day_second Number, -- second of the day,
count Number -- count of simultaneous calls
Your web service can take 'count' value from this table and make some statistics.
Simultaneous_calls table will be filled by some batch program which will be started every day after end of the day.
Assuming that you use Oracle, the batch may start a PL/SQL procedure which does the following:
Appends table with 24 * 3600 = 86400 records for each second of the day, with default 'count' value = 0.
Defines the 'day_cdrs' cursor for the query:
Select to_char(calldate, 'yyyymmdd') yyyymmdd,
(calldate - trunc(calldate)) * 24 * 3600 starting_second,
duration duration
From cdrs
Where cdrs.calldate >= Trunc(Sysdate -1)
And cdrs.calldate
Iterates the cursor to increment 'count' field for the seconds of the call:
For cdr in day_cdrs
Loop
Update simultaneos_calls
Set count = count + 1
Where yyyymmdd = cdr.yyyymmdd
And day_second Between cdr.starting_second And cdr.starting_second + cdr.duration;
End Loop;