This is similar to Compute dates and durations in mysql query, except that I don't have a unique ID column to work with, and I have samples not start/end points.
As an interesting experiment, I set cron to ps aux > 'date +%Y-%m-%d_%H-%M'.txt. I now have around 250,000 samples of "what the machine was running".
I would like to turn this into a list of "process | cmd | start | stop". The assumption is that a 'start' event is the first time when the pair existed, and a 'stop' event is the first sample where it stopped existing: there is no chance of a sample "missing" or anything.
That said, what ways exist for doing this transformation, preferably using SQL (on the grounds that I like SQL, and this seems like a nice challenge). Assuming that pids cannot be repeated this is a trivial task (put everything in a table, SELECT MIN(time), MAX(time), pid GROUP BY pid). However, since PID/cmd pairs are repeated (I checked, there are duplicates), I need a method that does a true "find all contiguous segments" search.
If necessary I can do something of the form
Load file0 -> oldList
ForEach fileN:
Load fileN ->newList
oldList-newList = closedN
newList-oldList = openedN
oldList=newList
But that is not SQL and not interesting. And who knows, I might end up having real SQL data to deal with with this property at some point.
I'm thinking something where one first constructs a table of diff's, and then joins all close's against all open's and pulls the minimum-distance close after each open, but I'm wondering if there's a better way.
You don't mention what database you are using. Let me assume that you are using a database that supports ranking functions, since that simplifies the solution.
The key to solving this is an observation. You want to assign an id to each pid to see if it is unique. I am going to assume that a pid represents a single process when the pid did not appear in the previous timestamped output.
Now, the idea is:
Assign a sequential number to each set of output. The first call to ps gets 1, the next 2, and so on, based on date.
Assign a sequential number to each pid, based on date. The first appearance gets 1, the next 2, and so on.
For pids that appear in sequence, the difference is a constant. We can call this the groupid for that set.
So, this is the query in action:
select groupid, pid, min(time), max(time)
from (select t.*,
(dense_rank() over (order by time) -
row_number() over (partition by pid order by time)
) as groupid
from t
) t
group by groupid, pid
This works in most databases (SQL Server, Oracle, DB2, Postgres, Teradata, among others). It does not work in MySQL because MySQL does not support the window/analytic functions.
Related
Here I have this query that finds out the drop percentage of a bunch of clients based on the orders they have received(i.e. It finds the percentage difference in orders by comparing the current month with the previous month). What I want to achieve here is to have a field where I can see the clients who had 4 months continuous drop, 3 months drop, 2 months drop, and 1 month drop.
I know, it can only be achieved by comparing the last 4 months using the lag function or sub queries. can you guys pls help me out on this one, would appreciate it very much
select
fd.customers2, fd.Month1, fd.year1, fd.variance, case when
(fd.variance < -0.00001 and fd.year1 = '2022.0' and fd.Month1 = '1')
then '1month drop' else fd.customers2 end as 1_most_host_drop
from
(SELECT
c.*,
sa.customers as customers2,
sum(sa.order) as orders,
date_part(mon, sa.date) as Month1,
date_part(year, sa.date) as year1,
(cast(orders - LAG(orders) OVER(Partition by customers2 ORDER BY
year1, Month1) as NUMERIC(10,2))/NULLIF(LAG(orders)
OVER(partition by customers2 ORDER BY year1, Month1) * 1, 0)) AS variance
FROM stats sa join (select distinct
d.id, d.customers
from configer d
) c on sa.customers=c.customers
WHERE sa.date >= '2021-04-1'
GROUP BY Month1, sa.customers, c.id, year1,
c.customers)fd
In a spirit of friendliness: I think you are a little premature in posting this here as there are several issues with the syntax before even reaching the point where you can solve the problem:
You have at least two places with a comma immediately preceding the word FROM:
...AS variance, FROM stats_archive sa ...
...d.customers, FROM config d...
Recommend you don't use VARIANCE as an alias (it is a system function in PostgreSQL and so is likely also a system function name in Redshift)
Not super important, but there's no need for c.* - just select the columns you will use
DATE_PART requires a string as the first parameter DATE_PART('mon',current_date)
I might be wrong about this, but I suspect you cannot use column aliases in the partition by or order by of a window function. Put the originating expressions there instead:
... OVER (PARTITION BY customers2 ORDER BY DATE_PART('year',sa.date),DATE_PART('mon',sa.date))
LAG has three parameters. (1) The column you want to retrieve the value from, (2) the row offset, where a positive integer indicates how many rows prior to the current row you should retrieve a value from according to the partition and order context and (3) the value the function should return as a default (in case of the first row in the partition). As such, you don't need NULLIF. So, to get the row immediately prior to the current row, or return 0 in case the current row is the first row in the partition:
LAG(orders,1,0) OVER (PARTITION BY customers2 ORDER BY DATE_PART('year',sa.date),DATE_PART('mon',sa.date))
If you use 0 as a default in the calculation of what is currently aliased variance, you will almost certainly run into a div/0 error either now, or worse, when you least expect it in the future. You should protect against that with some CASE logic or better, provide a more appropriate default value or even better, calculate the LAG with the default 0, then filter out the 0 rows before doing the calculation.
You can't use column aliases in the GROUP BY. You must reference each field that is not participating in an aggregate in the group by, whether through direct mention (sa.date) or indirectly in an expression (DATE_PART('mon',sa.date))
Your date should be '2021-04-01'
All in all, without sample data, expected results using the posted sample data and without first removing syntax errors, it is a tall order to attempt to offer advice on the problem which is any more specific than:
Build the source of the calculation as a completely separate query first. Calculate the LAG in that source query. Only when you've run that source query and verified that the LAG is producing the correct result should you then wrap it as a sub-query or CTE (not sure if Redshift supports these, but presumably) at which point you can filter out the rows with a zero as the denominator (the first month of orders for each customer).
Good luck!
I have the following MYSQL table:
measuredata:
- ID (bigint)
- timestamp
- entityid
- value (double)
The table contains >1 billion entries. I want to be able to visualize any time-window. The time window can be size of "one day" to "many years". There are measurement values round about every minute in DB.
So the number of entries for a time-window can be quite different. Say from few hundrets to several thousands or millions.
Those values are ment to be visualiuzed in a graphical chart-diagram on a webpage.
If the chart is - lets say - 800px wide, it does not make sense to get thousands of rows from database if time-window is quite big. I cannot show more than 800 values on this chart anyhow.
So, is there a way to reduce the resultset directly on DB-side?
I know "average" and "sum" etc. as aggregate function. But how can I i.e. aggregate 100k rows from a big time-window to lets say 800 final rows?
Just getting those 100k rows and let the chart do the magic is not the preferred option. Transfer-size is one reason why this is not an option.
Isn't there something on DB side I can use?
Something like avg() to shrink X rows to Y averaged rows?
Or a simple magic to just skip every #th row to shrink X to Y?
update:
Although I'm using MySQL right now, I'm not tied to this. If PostgreSQL f.i. provides a feature that could solve the issue, I'm willing to switch DB.
update2:
I maybe found a possible solution: https://mike.depalatis.net/blog/postgres-time-series-database.html
See section "Data aggregation".
The key is not to use a unixtimestamp but a date and "trunc" it, avergage the values and group by the trunc'ed date. Could work for me, but would require a rework of my table structure. Hmm... maybe there's more ... still researching ...
update3:
Inspired by update 2, I came up with this query:
SELECT (`timestamp` - (`timestamp` % 86400)) as aggtimestamp, `entity`, `value` FROM `measuredata` WHERE `entity` = 38 AND timestamp > UNIX_TIMESTAMP('2019-01-25') group by aggtimestamp
Works, but my DB/index/structue seems not really optimized for this: Query for last year took ~75sec (slow test machine) but finally got only a one value per day. This can be combined with avg(value), but this further increases query time... (~82sec). I will see if it's possible to further optimize this. But I now have an idea how "downsampling" data works, especially with aggregation in combination with "group by".
There is probably no efficient way to do this. But, if you want, you can break the rows into equal sized groups and then fetch, say, the first row from each group. Here is one method:
select md.*
from (select md.*,
row_number() over (partition by tile order by timestamp) as seqnum
from (select md.*, ntile(800) over (order by timestamp) as tile
from measuredata md
where . . . -- your filtering conditions here
) md
) md
where seqnum = 1;
I'm trying to query my database to pull only duplicate/old data to write to a scratch section in excel (Using a macro passing SQL to the DB).
For now, I'm currently testing in Access alone to only filter out the old data.
First, I'm trying to filter my database by a specifed WorkOrder, RunNumber, and Row.
The code below only filters by Work Order, RunNumber, and Row. ...but SQL doesn't like when I tack on a 2nd AND statement; so this currently isn't working.
SELECT *
FROM DataPoints
WHERE (((DataPoints.[WorkOrder])=[WO2]) AND ((DataPoints.[RunNumber])=6) AND ((DataPoints.[Row]=1)
Once I figure that portion out....
Then if there is only 1 entry with specified WorkOrder, RunNumber, and Row, then I want filter it out. (its not needed in the scratch section, because its data is already written to the main section of my report)
If there are 2 or more entries with said criteria(WO, RN, and Row), then I want to filter out the newest entry based on RunDate and RunTime, and only keep all older entries.
For instance, in the clip below. The only item remaining in my filtered query will be the top entry with the timestamp 11:47:00AM.
.
Are there any recommended commands to complete this problem? Any ideas are helpful. Thank you.
I would suggest something along the lines of the following:
select t.*
from datapoints t
where
t.workorder = [WO2] and
t.runnumber = 6 and
t.row = 1 and
exists
(
select 1
from datapoints u
where
u.workorder = t.workorder and
u.runnumber = t.runnumber and
u.row = t.row and
(u.rundate > t.rundate or (u.rundate = t.rundate and u.runtime > t.runtime))
)
Here, if the correlated subquery within the where clause finds a record with the same workorder, runnumber and row, but with either a later rundate or the same rundate and a later runtime, then the record is returned by the main query.
You need two more )'s at the end of your code snippet. Or you can delete the parentheses completely in this example, MS Access will ad them back in as it deems necessary.
M.S. Access SQL can be tricky as it is not standards compliant and either doesn't allow for super complex queries, or it needs an ugly work around, like having a parentheses nesting nightmare when trying to join more than two tables.
For these reasons, I suggest using multiple Access queries to produce your results.
I'm trying to calculate a cumulative total for a field for each row in a table.
Consider a number of passengers on a bus, I know how many people get on & off at each stop, but i need to add to this the load on the bus, arriving at each stop.
I've got as far as getting a field which will calculate how the load changes at each stop, but how do I get the load from the stop before it? note, there are a number of trips within the same table, so for Stop 1 on a new trip, the load would be zero.
I've tried searching, but being new to this, I'm not even sure what i should be looking for and the results I do get I'm not even sure are relevant!
SELECT [Tripnumber], [Stop], Sum([Boarders] - [Alighters]) AS LoadChange
FROM table
Group By [Tripnumber], [Stop], [Boarders], [Alighters]
Order By [Tripnumber], [Stop]
You can use window functions:
SELECT [Tripnumber], [Stop],
Sum([Boarders] - [Alighters]) OVER (PARTITION BY tripnumber ORDER BY Stop) As LoadChange
FROM table;
I don't think the GROUP BY is necessary.
Is an unbounded query a query without a WHERE param = value statement?
Apologies for the simplicity of this one.
An unbounded query is one where the search criteria is not particularly specific, and is thus likely to return a very large result set. A query without a WHERE clause would certainly fall into this category, but let's consider for a moment some other possibilities. Let's say we have tables as follows:
CREATE TABLE SALES_DATA
(ID_SALES_DATA NUMBER PRIMARY KEY,
TRANSACTION_DATE DATE NOT NULL
LOCATION NUMBER NOT NULL,
TOTAL_SALE_AMOUNT NUMBER NOT NULL,
...etc...);
CREATE TABLE LOCATION
(LOCATION NUMBER PRIMARY KEY,
DISTRICT NUMBER NOT NULL,
...etc...);
Suppose that we want to pull in a specific transaction, and we know the ID of the sale:
SELECT * FROM SALES_DATA WHERE ID_SALES_DATA = <whatever>
In this case the query is bounded, and we can guarantee it's going to pull in either one or zero rows.
Another example of a bounded query, but with a large result set would be the one produced when the director of district 23 says "I want to see the total sales for each store in my district for every day last year", which would be something like
SELECT LOCATION, TRUNC(TRANSACTION_DATE), SUM(TOTAL_SALE_AMOUNT)
FROM SALES_DATA S,
LOCATION L
WHERE S.TRANSACTION_DATE BETWEEN '01-JAN-2009' AND '31-DEC-2009' AND
L.LOCATION = S.LOCATION AND
L.DISTRICT = 23
GROUP BY LOCATION,
TRUNC(TRANSACTION_DATE)
ORDER BY LOCATION,
TRUNC(TRANSACTION_DATE)
In this case the query should return 365 (or fewer, if stores are not open every day) rows for each store in district 23. If there's 25 stores in the district it'll return 9125 rows or fewer.
On the other hand, let's say our VP of Sales wants some data. He/she/it isn't quite certain what's wanted, but he/she/it is pretty sure that whatever it is happened in the first six months of the year...not quite sure about which year...and not sure about the location, either - probably in district 23 (he/she/it has had a running feud with the individual who runs district 23 for the past 6 years, ever since that golf tournament where...well, never mind...but if a problem can be hung on the door of district 23's director so be it!)...and of course he/she/it wants all the details, and have it on his/her/its desk toot sweet! And thus we get a query that looks something like
SELECT L.DISTRICT, S.LOCATION, S.TRANSACTION_DATE,
S.something, S.something_else, S.some_more_stuff
FROM SALES_DATA S,
LOCATIONS L
WHERE EXTRACT(MONTH FROM S.TRANSACTION_DATE) <= 6 AND
L.LOCATION = S.LOCATION
ORDER BY L.DISTRICT,
S.LOCATION
This is an example of an unbounded query. How many rows will it return? Good question - that depends on how business conditions were, how many location were open, how many days there were in February, etc.
Put more simply, if you can look at a query and have a pretty good idea of how many rows it's going to return (even though that number might be relatively large) the query is bounded. If you can't, it's unbounded.
Share and enjoy.
http://hibernatingrhinos.com/Products/EFProf/learn#UnboundedResultSet
An unbounded result set is where a query is performed and does not explicitly limit the number of returned results from a query. Usually, this means that the application assumes that a query will always return only a few records. That works well in development and in testing, but it is a time bomb waiting to explode in production.
The query may suddenly start returning thousands upon thousands of rows, and in some cases, it may return millions of rows. This leads to more load on the database server, the application server, and the network. In many cases, it can grind the entire system to a halt, usually ending with the application servers crashing with out of memory errors.
Here is one example of a query that will trigger the unbounded result set warning:
var query = from post in blogDataContext.Posts
where post.Category == "Performance"
select post;
If the performance category has many posts, we are going to load all of them, which is probably not what was intended. This can be fixed fairly easily by using pagination by utilizing the Take() method:
var query = (from post in blogDataContext.Posts
where post.Category == "Performance"
select post)
.Take(15);
Now we are assured that we only need to handle a predictable, small result set, and if we need to work with all of them, we can page through the records as needed. Paging is implemented using the Skip() method, which instructs Entity Framework to skip (at the database level) N number of records before taking the next page.
But there is another common occurrence of the unbounded result set problem from directly traversing the object graph, as in the following example:
var post = postRepository.Get(id);
foreach (var comment in post.Comments)
{
// do something interesting with the comment
}
Here, again, we are loading the entire set without regard for how big the result set may be. Entity Framework does not provide a good way of paging through a collection when traversing the object graph. It is recommended that you would issue a separate and explicit query for the contents of the collection, which will allow you to page through that collection without loading too much data into memory.