I have a directory of companies provided to me they want stored and updated in a MySQL database. There is no unique identifier such as company #1234 for each company record.
The fields are typical for a mailing list, contact name, company name, street address, city, state, zip code, phone number and type of company. Updates will be sent to me as a CSV file, again, with no company unique identifier number.
How do I go about matching up the stored record in the db to the new one so it can be updated? In this industry the contact name can change, and even the company name because they add and subtract partners. Their street address can change because when they move the business, and they can even change their phone number. The majority of the companies have a website URL, so hopefully that won't change often but it easily could as well.
I've seen in MySQL there is a similar match %, would this be the answer to match records with the new information?
I work in PHP, if there is a PHP solution. Thanks in advance to the kind soul who helps me out with this!
Without primary key, it is always tricky.
One line solution, decide the rules to best suite your requirements.
If I were you, I first would go to the client to decide some rules of identifying similar records. This step is necessary as without primary key, as there is always a chance of duplicate entry or updating wrong record.
Rules could be simple like:
1. Available fileds:
contact name,
company name,
street address,
city,
state,
zip code,
phone number and
type of company (I Hope this is industry)
2. We will first match company name for similarity like
select * from table_name where company_name like '%$company_name%'
3. For all found records, match zip code and phone number. If match, break, record needs to be updated
4. If not match found in step 3, match street address. If match, break, record needs to be updated
5. & so on.
Your client is the best person to decide these rules as he is the owner of the product.
On the other side, asking rules from client is also important to keep you secure as in the absence of primary key, even after all the care, there is always a chance of duplicating records and/or updating wrong record. You could just minimize the chances with good rules.
As you have told that all the fields of the table can change then I think there is no simple way to correctly update the table every time whatever algorithm you choose.
One of the way to achieve this could be to ask the people/system (which sends you the updated records) to also include the old values of the updated fields in the csv file. If you have the old values you can easily match them with the present records and update it with the new values.
This is rather general question, but the solution itself is somewhat unique from project to project.
I would iterate over all records ordered by the time of their change (or a creating date or update timestamp or so). Next I'd match all entries with major fields similar: company name, address (though that might be risky), telephone or an url (parsing domains only). Then, I would recursively iterate over all found entries until no more results are found.
This algorithm would help to find you same entries as long as they do not have all major columns changes at once. If they do, there is no way saying it's the same firm programmatically.
This will link rows with seemingly now connections (rows 1 and 3 in example)
Example:
2001/01/01 Awesome firm, awesome.com
2002/02/02 Awesome firm, newaddress.com // linked with the first row over company name
2010/12/05 Ohsome inc, newaddress.com // linked over url
I have come acroos bit similar scenario in one of my earlier projects in Sql server.I used to do the following things to handle it.
1.Usually there will be 2 types of files--
a)Full feed (frequency weekly) this will have all the companies from the providers database
b)Incremental Feed(Frequency Daily) this will have only the new records which are not in full feed and updates.(inserts-I,updates -U as flags in incremental feeds)
2.So once I receive the full feed I will refresh the my database table with the full feed once in a week.Also here I will have my internal ids to each company record.(thses ids are for internal purpose)
3.On daily basis I process incremental feeds based on the flags(I-insert,U-update).
4.One very important thing here is to manage the mapping table.Once the feed comes just assign a new internal id to it.
5.For comparing the data to avoid duplicates,I used to use Fuzzy algorithm to get all the potential matches and then use wildcard characters to filter and identify which are new and duplicates.
Have a look at the Damerau-Levenshtein distance algorithm. It calculates the "distance" between two strings and determines how many steps it takes to transform one string into another. The less steps the closer the two strings are.
This article shows the algorithm implemented as a MySQL stored function. Here's the PHP version.
The algorithm is so much better than LIKE or SOUNDEX.
Related
I run a SQL database with some user information.
On the main page, I would like to throw some statistics about the database, and what I thought was easy at first, showed to be complicated for me (I'm a newbie).
To give a pratical example of what I'm trying to achieve, I will use a real situation to exemplify:
On my CLIENTS table, all of my clients are from different countries (represented by a country code). One of the statistics I'm trying to show, is WHAT COUNTRY HAS MORE CLIENTS.
Is there a simple way to find this kind of information? I understand I can simply count how many occurences of certain country I have on the TABLE, but I would need to compare with every country to check which on hosts more clients.
I guess that sums up my question.
EDIT: I came up with a solution but I'm just not sure if it's best, using PHP. I did a loop test for each country checking the number of clients, and compared to the one before. If the count was higher, I updated the $higher_country var, if not, I just moved to next country. Would that be my only option?
You can do something like...
SELECT country_id, count(country_id) as nmbr
FROM clients
group by country_id
order by nmbr desc
limit 1
This counts up the number of a specific value and orders it in reverse order (so highest first) and just picks the first record.
I am a field service technician and I have an inventory of parts that is either issued to me by the company I work for or through orders for specific jobs. I am trying to design a website to manage my parts, both on-hand inventory and parts that have been returned or transferred to someone else. Here is the information I need to track:
part number(10 digit)
req number(8 digit, unique)
description(up to 50 characters)
location(Van or shed).
WorkOrder("w"+9 digits ex: 'W212141234')
BOL(15 digit bill of lading #)
TransferDate(date I get rid of part)
TransferMethod(enum 'DEF','RTS','OBF')
I will probably use PHP to make a website and interact with the MySQL database.
What is the best design? A multi-table approach or one table with webpages that display queries of only certain fields? I need a list of on hand parts that list part number, req number, description, and location. I will also need to be able to have "defective returns" view that will list what parts I returned as DEF with all the remaining fields filled in.
Besides the "on hand" fields, the rest of the fields won't have data until they are no longer "on hand".
I really appreciate any help because I am new to both SQL and PHP. I have experimented with Ruby on Rails and django but I am not sure if I need to tackle all that at this point.
Even though you give some information on your issue, it is hard to actually approach it as the question itself on "what is the best design" is vague.
What I would do is this:
MYSQL TABLE DESIGN
Table parts
req number(int(8), unique, KEY)
part number(int(10))
description(varchar(50))
location(enum 'Van','shed')
WorkOrder(varchar(10))
BOL(varchar(15))
TransferDate(date)
TransferMethod(enum 'DEF','RTS','OBF')
onhand (boolean)
PHP SCRIPTS
and then i would make 2 php scripts with a single query each and a table displaying the info
onhand.php
select *fields filled for on hand parts* from parts where onhand = 1
notonhand.php
select *fields filled for not on hand parts* from parts where onhand = 0
Problem Overview:
My application has an enrollment form.
Users have a habit of entering the same person into the system twice.
I need to find a way to rapidly and accurately check the data they've entered against the other clients in the database to see if that client is already in the database.
Criteria Currently Being Used:
Duplicate SSN
Duplicate Last Name and Date of Birth
Duplicate First Name, Date Of Birth and Partial SSN Match (another client has an SSN where 5 of the 9 digits are the same and in the same position.
Duplicate First Name and Partial SSN Match (another client has an SSN where 5 of the 9 digits are the same and in the same position.
Duplicate Last Name and Partial SSN Match (another client has an SSN where 5 of the 9 digits are the same and in the same position.
In addition to these checks, there's been discussion of using soundex to detect matches based on similiar first name / last name.
Is there a PHP class already designed to handle something like this? Can something like this be done at a (Mysql) Database level?
Clarifications:
The problem exists not because of a lack of data integrity at the database level but because of typos caused during the entry process. The applicaiton is a data-entry application. Users are taking physical paper copies of forms and entering the data into the application.
If I understand your problem correctly the point is that the duplicates you want to filter out are not necessarely equal as strings. I encountered situations like this a couple of times in the past and I could never find a perfect criteria for finding logical duplicates. In my opinion the best way to deal with such cases is to provide a very smart autocomplete-like functionallity to the user, so when he tries to enter the data he sees all the similar entries and he hopefully won't create a new entry for something he see in the list. Such a soulution can be a good "buddy" of your not-yet-perfect criteria.
Not a php solution, but
You can cast that fields in your database as unique.
ALTER TABLE `users` ADD UNIQUE (
`username`
)
I've got a problem that I just can't seem to find the answer to. I've developed a very small CRM-like application in PHP that's driven by MySQL. Users of this application can import new data to the database via an uploaded CSV file. One of the issues we're working to solve right now is duplicate, or more importantly, near duplicate records. For example, if I have the following:
Record A: [1, Bob, Jones, Atlanta, GA, 30327, (404) 555-1234]
and
Record B: [2, Bobby, Jones, Atlanta, GA, 30327, Bob's Shoe Store, (404) 555-1234]
I need a way to see that these are both similar, take the record with more information (in this case record B) and remove record A.
But here's where it gets even more complicated. This must be done upon importing new data, and a function I can execute to remove duplicates from the database at any time. I have been able to put something together in PHP that gets all duplicate rows from the MySQL table and matches them up by phone number, or by using implode() on all columns in the row and then using strlen() to decide the longest record.
There has got to be a better way of doing this, and one that is more accurate.
Do any of you have any brilliant suggestions that I may be able to implement or build on? It's obvious that when importing new data I'll need to open their CSV file into an array or temporary MySQL table, do the duplicate/similar search, then recompile the CSV file or add everything from the temporary table to the main table. I think. :)
I'm hoping that some of you can point out something that I may be missing that can scale somewhat decently and that's somewhat accurate. I'd rather present a list of duplicates we're 'unsure' about to a user that's 5 records long, not 5,000.
Thanks in advance!
Alex
If I were you I'd give a UNIQUE key to name, surname and phone number since in theory if all these three are equal then it means that it is a duplicate. I am thinking so because a phone number can have only one owner. Anyways, you should find a combination of 2-3 or maybe 4 columns and assign them a unique key. Once you have such a structure, run something like this:
// assuming that you have defined something like the following in your CREATE TABLE:
UNIQUE(phone, name, surname)
// then you should perform something like:
INSERT INTO your_table (phone, name, surname) VALUES ($val1, $val2, $val3)
ON DUPLICATE KEY UPDATE phone = IFNULL($val1, phone),
name = IFNULL($val2, name),
surname = IFNULL($val3, surname);
So basically, if the inserted value is a duplicate, this code will update the row, rather than inserting a new one. The IFNULL function performs a check to see whether the first expression is null or not. If it is null, then it picks the second expression, which in this case is the column value that already exists in your table. Hence, it will update your row with as much as information possible.
I don't think there're brilliant solutions. You need to determine priority of your data fields you can rely on for detecting similarity, for example phone, some kind of IDs, of some uniform address or official name.
You can save some cleaned up values (reduced to the same format like only digits in phones, concatenated full address) along with row which you would be able to use for similarity search when adding records.
Then you need to decide on data completeness in any case to update existing rows with more complete fields, or delete old and add new row.
Don't know any ready solutions for such a variable task and doubt they exist.
Background
I am creating a MySQL database to store items such as courses where there may be many attributes to a single course. For example:
A single course may have any or all of the following attributes:
Title (varchar)
Secondary Title (varchar)
Description (text)
Date
Time
Specific Location (varchar; eg. White Hall Room 7)
General Location (varchar; eg. Las Vegas, NV)
Location Coords (floats; eg. lat, long)
etc.
The database is set up as follows:
A table storing specific course info:
courses table:
Course_ID (a Primary Key unique ID for each course)
Creator_ID (a unique ID for the creator)
Creation_Date (datetime of course creation)
Modified_Date (where this is the most recent timestamp the course was modified)
The table storing each courses multiple attributes is set up as follows:
course_attributes table:
Attribute_ID (a unique ID for each attribute)
Course_ID (reference to the specific course attribute is for)
Attribute (varchar definining the attribute; eg. 'title')
Value (text containing value of specified attribute; eg. 'Title Of My Course')
Desire
I would like to search this database using sphinx search. With this search, I have different fields weighing different amounts, for example: 'title' would be more important than 'description'.
Specific search fields that I wish to have are:
Title
Date
Location (string)
Location (geo - lat/long)
The Question
Should I define a View in Mysql to organize the attributes according to 'title', 'description', etc., or is there a way to define my sphinx.conf file to understand specific attributes?
I am open to all suggestions to solving this problem, whether it be rearrangement of the database/tables or the way in which I search.
Let me know if you need any additional details to help me find a solution.
Thanks in advance for the help
!--Update--!
OK, so after reading some of the answers, I feel that I should provide some additional information.
Latitude / Longitude
The latitude/longitude attributes are created by me internally after receiving the general location string. I can generate the values in any way I wish, meaning that I can store them together in a single lat/long attribute as 'float lat, float long' values or any other desired format. This is done only after they have been generated from the initial location string and verified. This is to guard against malformed data as #X-Zero and #Cody have suggested.
Keep in mind that the latitude and longitude was merely illustrating the need to have that field be searchable as opposed to anything more than that. It is simply another attribute; one of many.
Weighting Search Results
I know how to add weights to results in a Sphinx search query:
$cl->setFieldWeights( array('title'=>1000, 'description'=>500) );
This causes the title column to have a higher weight than the description column if the structure was as #X-Zero suggested. My question was more directed to how one would apply the above logic with the current table definition.
Database Structure, Views, and Efficiency
Using my introductory knowledge of Views, I was thinking that I could possibly create something that displays a row for each course where each attribute is its own column. I don't know how to accomplish this or if it's even possible.
I am not the most confident with database structures, but the reason I set my tables up as described was because there are many cases where not all of the fields will be completed for every course and I was attempting to be efficient [yes, it seems as though I've failed].
I was thinking that using my current structure, each attribute would contain a value and would therefore cause no wasted space in the table. Alternatively, if I had a table with tons of potential attributes, I would think there would be wasted space. If I am incorrect, I am happy to learn why my understanding is wrong.
Let me preface this by saying that I've never even heard of Sphinx, nor (obviously) used it. However, from a database perspective...
Doing multi-domain columns like this is a terrible (I will hunt you down and kill you) idea. For one thing, it's impossible to index or sort meaningfully, period. You also have to pray that you don't get a latitude attribute with textual data (and because this can only be reinforced programatically, I'm going to garuantee this will happen) - doing so will cause all distance based formulas to crash. And speaking of location, what happens if somebody stores a latitude without a longitude (note that this is possible regardless of whether you are storing a single GeoLocation attribute, or the pair)?
Your best bet is to do the following:
Figure out which attributes will always be required. These belong in the course table (...mostly).
For each related set of optional attributes, create a table. For example, location (although this should probably be required...), which would contain Latitude/Longitude, City, State, Address, Room, etc. Allow the columns to be nullable (in sets - add constraints so users can't add just longitude and not latitude).
For every set of common queries add a view. Even (perhaps especially) if you persist in using your current design, use a view. This promotes seperation between the logical and physical implementations of the database. (This assumes searching by SQL) You will then be able to search by specifying view_column is null or view_column = input_parameter or whichever.
For weighted searching (assuming dynamic weighting) your query will need to use left joins (inside the view as well - please document this), and use prepared-statement host-parameters (just save yourself the trouble of trying to escape things yourself). Check each set of parameters (both lat and long, for example), and assign the input weighting to a new column (per attribute), which can be summed up into a 'total' column (which must be over some threshold).
EDIT:
Using views:
For your structure, what you would normally do is left join to the attributes table multiple times (one for each attribute needed), keying off of the attribute (which should really be an int FK to a table; you don't want both 'title' and 'Title' in there) and joining on course_id - the value would be included as part of the select. Using this technique, it would be simple to then get the list of columns, which you can then apparently weight in Sphinx.
The problem with this is if you need to do any data conversion - you are betting that you'll be able to find all conversions if the type ever changes. When using strongly typed columns, this is between trivial (the likelyhood is that you end up with a uniquely named column) to unnecessary (views usually take their datatype definitions from the fields in the query); with your architecture, you'll likely end up looking through too many false positives.
Database efficiency:
You're right, unfilled columns are wasted space. Usually, when something is optional(ish), that means you may need an additional table. Which is Why I suggested splitting off location into it's own table: this prevents events which don't need a location (... what?) from 'wasting' the space, but then forces any event that defines a location to specify all required information. There's an additional benefit about splitting it off this way: if multiple events all use the same location (... not at the same time, we hope), a cross-reference table will save you a lot of space. Way more than your attributes table ever could (you're still having to store the complete location per event, after all). If you still have a lot of 'optional' attributes, I hear that NoSQL is made for these kinds of things (but I haven't really looked into it). However, other than that, the cost of an additional table is trivial; the cost of the data inside may not be, but the space required is weighed against the perceived value of the data stored. Remember that disk space is relatively cheap - it's developer/maintainer time that is expensive.
Side note for addresses:
You are probably going to want to create an address table. This would be completely divorced from the event information, and would include (among other things) the precomputed latitude/longitude (in the recommended datatype - I don't know what it is, but it's for sure not a comma-separated string). You would then have an event_address table that would be the cross-reference between the events and where they take place - if there is additional information (such as room), that should be kept in a location table that is referenced (instead of referencing address directly). Once a lat/long value is computed, you should never need to change it.
Thoughts on later updates for lat/long:
While specifying the lat/long values yourself is better, you're going to want to make them a required part of the address table (or part of/in addition to a purely lat/long only table). Frankly, multi-value columns (delimited lists) of any sort are just begging for trouble - you keep having to parse them every time you search on them (among other related issues). And the moment you make them separate rows, one of the pair will eventually get dropped - Murphy himself will personally intervene, if necessary. Additionally, updating them at different times from the addresses will result in an address having a lat/long pair that does not match; your best bet is to compute this at insertion time (there are a number of webservices to find this information for you).
Multi-domain tables:
With a multi-domain table, you're basically betting that the domain key (attribute) will never become out-of-sync with the value (err, value). I don't care how good you are, somewhere, somehow, it's going to happen: at my company, we had one of these in our legacy application (it stored FK links and which files the FKs refer to, along with an attribute). At one point an application was installed in production which promptly began storing the correct file links, but the FK links to a different file, for a given class of attribute. Thankfully, there were audit records in another file which allowed this to be reversed (... as near as they were able tell).
In summary:
Revisit your required/optional data. Don't be afraid to create additional tables, each for a single entity, with every column for a single domain; you will also need relationship tables. You may also wish to place your audit data (last_updated_time) in a set of separate tables (single-domain tables will help immensely in this regard).
In the sphinx config you define your index and the SQL queries that populate it. You can define basic attributes, see Sphinx Attributes
Sphinx also supports geo searches on lat/long but they need to be expressed in radians, definitely not text columns like you have. I agree with X-Zero that storing lat/lng values are strings is a bad idea.