I have the below array to detect 3 different criteria and return multiple results from a data source with 10000 Rows.
{=IF(INDEX(Inventory!$A$3:$Q$10000;SMALL(IF(($C$4=Inventory!$A$3:$A$10000)*($C$3=Inventory!$E$3:$E$10000)*(Inventory!$F$3:$F$10000="NEW");ROW(Inventory!$A$3:$A$10000)-ROW($C$3)+2);ROW(Inventory!1:1));16)=0;"";INDEX(Inventory!$A$3:$Q$10000;SMALL(IF(($C$4=Inventory!$A$3:$A$10000)*($C$3=Inventory!$E$3:$E$10000)*(Inventory!$F$3:$F$10000="NEW");ROW(Inventory!$A$3:$A$10000)-ROW($C$3)+2);ROW(Inventory!1:1));16))}
The Inventory table goes like this
A |E |F |P
Standard Laptop |Lisbon |NEW |XCVBMT
Engineering Laptop |London |DAMAGED |CVFTYU
Multiple Vendor |Madrid |QUARANTINE |CVBLPU
Standard Laptop |Lisbon |NEW |JKHGLK
I Have A and E criteria to select from drop down lists in C3 and C4.
If I delete the below criteria from the array, it works:
($C$4=Inventory!$A$3:$A$10000)
I cleared all formats, changed rows, changed the criteria to D4 and tiped in manually, trimmed... I think is right in front of me but have no clue on whats wrong.
I hope this is enough information.
Thanks
I have to create a database combined with 4 types of xls files, for example A, B, C and D. Every year new file is created, starting from 2004. A have 7 sheets with 800-1000 rows, B - D have one sheet with max 200 rows.
Everyone knows that people are lazy, so in excel files, address data are stored differently in each sheet. One of them, from 2008, have address data stored separately, but every other sheets have this data combined into one column.
Sooo, here is a question - how should I design a datatable? Something like this?
+---------+----------+----------+-------------+--------------------------------+
| Street | House Nr | City | Postal Code | Combined Address |
+---------+----------+----------+-------------+--------------------------------+
| Street1 | 20 | Somwhere | 00-000 | null |
| Street2 | 98 | Elswhere | 99-999 | null |
| null | null | null | null | Somwhere 00-000, street3 29 |
| null | null | null | null | st. Street2 65 12-345 Elswhere |
+---------+----------+----------+-------------+--------------------------------+
There will be a lot of nulls, so maybe best solution would be 2 different tables?
Most important thing is that users will search by using this data, and in the future add data into that database without excel files.
There are at least two different angles of view here: Normalization and efficiency, leading to different results.
Normalization
If this is the most important criterion you would make even three tables. Obviously Combined Address needs a place of it's own, but also Postal Code and City have to be stored into another table, because there is a dependency between them. Just one of the two, most probably Postal Code will stay. (Yes, there even is sth. about Street and Postal Code too, but I'm clearly not going to be pedantic.)
Efficiency
Normalization as an end in itself doesn't necessarily make the best result. If you permit yourself to be a bit sloppy on that and leave it the way it is in the model you posted, things might become easier in coding. You could use a trigger to make sure Combined Address is never null or use a (materialized) view that pretends it is and just search in Combined Address for the time being.
Imagine the effort if you use different tables and there is a need for referencing these addresses in other tables (Which table to use when? How to provide a unique id? Clearly a problem.).
So, decide on what's more important.
If I'm not mistaken we are taking about some 2000 rows or some 8000 rows if it is '7 sheets with 800-1000 rows each' actually. Even if the latter applies this isn't a number that makes data correction impracticable. If the number of different input pattern in the combined column is low, you might be able to do this (partly) automatically and just have some-one prove reading.
So you might want to think about a future redesign as well and choose what's more convenient in this case.
I'm looking for an efficient way of storing sets of objects that have occurred together during events, in such a way that I can generate aggregate stats on them on a day-by-day basis.
To make up an example, let's imagine a system that keeps track of meetings in an office. For every meeting we record how many minutes long it was and in which room it took place.
I want to get stats broken down both by person as well as by room. I do not need to keep track of the individual meetings (so no meeting_id or anything like that), all I want to know is daily aggregate information. In my real application there are hundreds of thousands of events per day so storing each one individually is not feasible.
I'd like to be able to answer questions like:
In 2012, how many minutes did Bob, Sam, and Julie spend in each conference room (not necessarily together)?
Probably fine to do this with 3 queries:
>>> query(dates=2012, people=[Bob])
{Board-Room: 35, Auditorium: 279}
>>> query(dates=2012, people=[Sam])
{Board-Room: 790, Auditorium: 277, Broom-Closet: 71}
>>> query(dates=2012, people=[Julie])
{Board-Room: 190, Broom-Closet: 55}
In 2012, how many minutes did Sam and Julie spend MEETING TOGETHER in each conference room? What about Bob, Sam, and Julie all together?
>>> query(dates=2012, people=[Sam, Julie])
{Board-Room: 128, Broom-Closet: 55}
>>> query(dates=2012, people=[Bob, Sam, Julie])
{Board-Room: 22}
In 2012, how many minutes did each person spend in the Board-Room?
>>> query(dates=2012, rooms=[Board-Room])
{Bob: 35, Sam: 790, Julie: 190}
In 2012, how many minutes was the Board-Room in use?
This is actually pretty difficult since the naive strategy of summing up the number of minutes each person spent will result in serious over-counting. But we can probably solve this by storing the number separately as the meta-person Anyone:
>>> query(dates=2012, rooms=[Board-Room], people=[Anyone])
865
What are some good data structures or databases that I can use to enable this kind of querying? Since the rest of my application uses MySQL, I'm tempted to define a string column that holds the (sorted) ids of each person in the meeting, but the size of this table will grow pretty quickly:
2012-01-01 | "Bob" | "Board-Room" | 2
2012-01-01 | "Julie" | "Board-Room" | 4
2012-01-01 | "Sam" | "Board-Room" | 6
2012-01-01 | "Bob,Julie" | "Board-Room" | 2
2012-01-01 | "Bob,Sam" | "Board-Room" | 2
2012-01-01 | "Julie,Sam" | "Board-Room" | 3
2012-01-01 | "Bob,Julie,Sam" | "Board-Room" | 2
2012-01-01 | "Anyone" | "Board-Room" | 7
What else can I do?
Your question is a little unclear because you say you don't want to store each individual meeting, but then how are you getting the current meeting stats (dates)? In addition any table given the right indexes can be very fast even with alot of records.
You should be able to use a table like log_meeting. I imagine it could contain something like:
employee_id, room_id, date (as timestamp), time_in_meeting
Where foreign keys to employee id to employee table, and room id key to room table
If you index employee id, room id, and date you should have a pretty quick lookup as mysql multiple-column indexes go left to right such that you gain index on (employee id, employee id + room id, and employee id + room id + timestamp) when do searches. This is explained more in the multi-index part of:
http://dev.mysql.com/doc/refman/5.0/en/mysql-indexes.html
By refusing to store meetings (and related objects) individually, you are loosing the original source of information.
You will not be able to compensate for this loss of data, unless you memorize on a regular basis the extensive list of all potential daily (or monthly or weekly or ...) aggregates that you might need to question later on!
Believe me, it's going to be a nightmare ...
If the number of people are constant and not very large you can then assign a column to each person for present or not and store the room, date and time in 3 more columns this can remove the string splitting problems.
Also by the nature of your question I feel first of all you need to assign Ids to everything rooms,people, etc. No need for long repetitive string in DB. Also try reducing any string operation and work using individual data in each column for better intersection performance. Also you can store a permutation all the people in a table and assign a id for them then use one of those ids in the actual date and time table. But all techniques will require that something be constant either people or rooms.
I do not understand whether you know all "questions" in design time or it's possible to add new ones during development/production time - this approach would require to keep all data all the time.
Well if you would know all your questions it seems like classic "banking system" which recalculates data on daily basis.
How I think about it.
Seems like you have limited number of rooms, people, days etc.
Gather logging data on daily basis, one table per day. Just one event, one database row, all information (field) what you need.
Start to analyse data using some crone script at "midnight".
Update stats for people, rooms, etc. Just increment number of hours spent by Bob in xyz room etc. All what your requirements need.
As analyzed data are limited and relatively small as you analyzed (compress) them, your system can contain also various queries as indexes would be relatively small etc.
You could be able to use scalable map/reduce algorithm.
You can't avoid storing the atomic facts as follows: (the meeting room, the people, the duration, the day), which is probably only a weak consolidation when the same people meet multiple times in the same room on the same day. Maybe that happens a lot in your office :).
Making groups comparable is an interesting problem, but as long as you always compose the member strings the same, you can probably do it with string comparisons. This is not "normal" however. To normalise you'll need a relation table (many to many) and compose a temporary table out of your query set so it joins quickly, or use an "IN" clause and a count aggregate to ensure everyone is there (you'll see what I mean when you try it).
I think you can derive the minutes the board room was in use as meetings shouldn't overlap, so a sum will work.
For storage efficiency, use integer keys for everything with lookup tables. Dereference the integers during the query parsing, or just use good old joins if you are feeling traditional.
That's how I would do it anyway :).
You'll probably have to store individual meetings to get the data you need anyway.
However you'll have to make sure you aggregate and anonymise it properly before creating your reports. Make sure to separate concerns and access levels to stay within the proper legal limits on data.
I have a rather large amount of data (~400 mio datapoints) which is organized in a set of ~100,000 timecourses. This data may change every day and for reasons of revision-safety has to be archived daily.
Obviously we are talking about way too much data to be handled efficiently, so I made some analysis on sample data. Approx. 60 to 80% of the courses do not change at all between two days and for the rest only a very limited amount of the elements changes. All in all I expect much less than 10 mio datapoints change.
The question is, how do I make use of this knowledge? I am aware of concepts like the Delta-Trees used by SVN and similar techniques, however I would prefer, if the database itself would be capable of handling such semantic compression. We are using Oracle 11g for storage and the question is, is there a better way than a homebrew solution?
Clarification
I am talking about timecourses representing hourly energy-currents. Such a timecourse might start in the past (like 2005), contains 8760 elements per year and might end any time up to 2020 (currently). Each timecourse is identified by one unique string.
The courses themselves are more or less boring:
"Course_XXX: 1.1.2005 0:00 5; 1.1.2005 1:00 5;1.1.2005 2:00 7,5;..."
My task is making day-to-day changes in these courses visible and to do so, each day at a given time a snapshot has to be taken. My hope is, that some loss-free semantical compression will spare me from archiving ~20GB per day.
Basically my source data looks like this:
Key | Value0 | ... | Value23
to archive that data I need to add an additional dimension which directly or indirectly tells me the time at which the data was loaded from the source-system, so my archive-database is
Key | LoadID | Value0 | ... | Value23
Where LoadID is more or less the time the source-DB was accessed.
Now, compression in my scenario is easy. LoadIDs are growing with each run and I can give a range, i.e.
Key | LoadID1 | LoadID2 | Value0 | ... | Value23
Where LoadID1 gives me the ID of the first load where the 24 values where observed and LoadID2 gives me the ID of the last consecutive load where the 24 values where observed.
In my scenario, this reduces the amount of data stored in the database to 1/30th
I have an Excel document with 10000 rows of data in two sheets, the thing is one of these sheets have the product costs, and the other has category and other information. These two are imported automatically from the sql server so I don't want to move it to Access but still I want to link the product codes so that when I merge the product tables as product name and cost on the same table, I can be sure that I'm getting the right information.
For example:
Code | name | category
------------------------------
1 | mouse | OEM
4 | keyboard | OEM
2 | monitor | screen
Code | cost |
------------------------------
1 | 123 |
4 | 1234 |
2 | 1232 |
7 | 587 |
Let's say my two sheets have tables like these, as you can see the next one has one that doesn't exist on the other- I put it there because in reality one has a few more, preventing a perfect match. Therefore I couldn't just sort both tables to A-Z and get the costs that way- as I said there are more than 10000 products in that database and I wouldn't want to risk a slight shift of costs -with those extra entries on the other table- that would ruin the whole table.
So what would be a good solution to get the entry from another sheet and inserting it to the right row when merging? Linking two tables with field name??... checking field and trying to match it with the other sheet??... Anything at all.
Note: When I use Access I would make relationships and when I would run a query it would match them automatically... I was wondering if there's a way to do that in excel too.
Why not use a vlookup? If there is a match, it will list the cost. Assuming the top is sheet1 and the other sheet2 and they both start on cell A1. You just need this in cell D2.
=VLOOKUP(A2,Sheet2!A:B,2,0)
You can then drag it down. Easiest way to fill all your 10000 rows is to hover over the bottom left corner of the cell with your cursor. It will turn from a white plus sign into a thin black one. Then simply double click.
Just use VLOOKUP - you can add a row to your first sheet, and find the cost based on code in the other sheet.