I only found answers about how to import csv files into the database, for example as blob or as 1:1 representation of the table you are importing it into.
What I need is a little different: My team and I are tracking everything we do in a database. A lot of these tasks produce logfiles, benchmark results, etc., which are stored in CSV format. The number of columns are far from consistent and also the data could be completely different from file to file, e.g. it could be a log from fraps with frametimes in it or a log of CPU temparatures over an amount of time, or even something completely different.
Long story short, I came up with an idea, but - being far from a sql pro - I am not sure if it makes sense or if there is a more elegant solution.
Does this make sense to you:
We also need to deal with a lot of data that is produced, so please give me also your opinion if that is feasible with like 200 files per day which can easyly have a couple of thousands rows.
The purpose of all this will be, that we can generate reports form the stored data and perform analysis of the data. E.g. view it on a webpage in a graph or do calculations with it.
I'm limited to MS-SQL in this case, because that's what the current (quite complex) database is and I'm just adding a new schema with that functionality to it.
Currently we just archive the files on a raid and store a link to it in the database. So everyone who wants to do magic with the data needs to download every file he needs and then use R or Excel to create a visualization of the data.
Have you considered a column of XML data type for the file data as an alternative of ColumnId -> Data structure? SQL server provides is a special dedicated XML index (over the entire XML structure) so your data can be fully indexed no matter what CSV columns you have. You will have much less records in the database to handle (as an entire CSV file will be a single XML field value). There are good XML query options to search by values & attributes of the XML type.
For that you will need to translate CSV to XML, but you will have to parse it either way ...
Not that your plan won't work, I am just giving an idea :)
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Update with some online info:
An article from Simple talk: The XML Methods in SQL Server
Microsoft documentation for nodes() with various use case samples: nodes() Method (xml Data Type)
Microsoft document for value() with various use case samples: value() Method (xml Data Type)
Related
I have an extremely large CSV, where each row contains customer and store ids, along with transaction information. The current test file is around 40 GB (about 2 days worth), so partitioning is an absolute must for any reasonable return time on select queries.
My question is this: When we receive a file, it contains multiple store's data. I would like to use the "virtual column" functionality to separate this file into the respective directory structure. That structure is "/Data/{CustomerId}/{StoreID}/file.csv".
I haven't yet gotten it to work with the OUTPUT statement. The statement use was thus:
// Output to file
OUTPUT #dt
TO #"/Data/{CustomerNumber}/{StoreNumber}/PosData.csv"
USING Outputters.Csv();
It gives the following error:
Bad request. Invalid pathname. Cosmos Path: adl://<obfuscated>.azuredatalakestore.net/Data/{0}/{1}/68cde242-60e3-4034-b3a2-1e14a5f7343d
Has anyone attempted the same kind of thing? I tried to concatenate the outputpath from the fields, but that was a no-go. I thought about doing it as a function (UDF) that takes the two ID's and filters the whole dataset, but that seems terribly inefficient.
Thanks in advance for reading/responding!
Currently U-SQL requires that all the file outputs of a script must be understood at compile time. In other words, the output files cannot be created based on the input data.
Dynamic outputs based on data are something we are actively working for release sometime later in 2017.
In the meanwhile until the dynamic output feature is available, the pattern to accomplish what you want requires using two scripts
The first script will use GROUP BY to identify all the unique combinations of CustomerNumber and StoreNumber and write that to a file.
Then through the use of scripting or a tool written using our SDKs, download the previous output file and then programmatically create a second U-SQL script that has an explicit OUTPUT statement for each pair of CustomerNumber and StoreNumber
I was bored and looking at old code that runs like molasses on a cold day. I found that a group of tables in our accounting system - each with 500,000 records of ~20 datapoints - that use a single column of concatenated, fixed-width values instead of separate columns. (Fixing the tables isn't an option.) An old .net ETL project is grabbing all records, doing a bunch of substrings on each record to set an object's corresponding attributes, then sending the object to merge with production data via a stored proc.
The way it is working is fine. It works. And, to be perfectly honest, I doubt I'll be given the go-ahead to fix it even if I come up with a better solution, but I was curious to see if anyone knew of a better way of doing this, because it's not entirely unlikely that I'll face a situation like this in the future.
I was thinking that if there was a way to use the TextFieldParser to parse a static string instead of a file/stream that might be a valid idea. Or, instead, I could write the entire table to a text file and then use the TextFieldParser to send data to the SProc. http://www.dotnetperls.com/textfieldparser does show that TextFieldParser is quite a bit faster than split, which I would assume is tantamount to the string manipulation our project is currently doing with substring. So there may be something to that idea.
Or perhaps the whole, old project should be dumped for a shiny new SSIS project. Would it also have to write the records to a flat file before importing into SQL? Or can it import directly from the table?
Thank you in advance!
I have an XML feed of a resume. Each part of the resume is broken down into its constituent parts. For example <employment_history>, <education>, <skills>.
I am aware that I could save each section of the XML file into a database. For example columnID = employment_history | education | skills & then conduct a free text search just on those individual columns. However I would prefer not to do this because it would create duplication of data that is already contained within the XML file and may put extra strain on indexing.
Therefore I wondered if it is possible to conduct a free text search of an XML file within the <employment_history></employment_history> using SQL Server.
If so an example would be appreciated.
Are you aware that SQL Server supports columns with the data type of "XML"? These can contain an entire XML document.
You can also index these columns and you can use XQuery to perform query and data manipulation tasks on those columns.
See Designing and Implementing Semistructured Storage (Database Engine)
Querying xml by doing string searching using sql is probably going to run into a lot of trouble.
Instead, I would parse it into whatever language you're using to interact with your database and use xpath (most languages/environments have some kind of built in or popular 3rd party library) to query it.
I think you can create a function (UDF) that takes the xml text as a parameter then it fetches the data inside tag then you make the filter you want
I have a table called Animals. I pull data from this table to populate another system.
I get Excel data with lists of animals that need to go in the Animals table.
The Excel data will also have other identifiers, like Breed, Color, Age, Favorite Toy, Veterinarian, etc.
These identifiers will change with each new excel file. Some may repeat, others are brand new.
Because the fields change, and I never know what new fields will come with each new excel file, my Animals table only has Animal Id and Animal Name.
I've created a Values table to hold all the other identifier fields. That table is structured like this:
AnimalId
Value
FieldId
DataFileId
And then I have a Fields table that holds the key to each FieldId in the Values table.
I do this because the alternative is to keep a big table with fields that may not even be used each time I need to add data. A big table with a lot of null columns.
I'm not sure my way is a good way either. It can seem overly complex.
But, assuming it is a good way, what is the best way to get this excel data into my Values table? The list of animals is easy to add to my Animals table. But for each identifier (Breed, Color, etc.) I have to copy or import the values and then update the table to assign a matching FieldId (or create a new FieldId in the Fields table if it doesn't exist yet).
It's a huge pain to load new data if there are a lot of identifiers. I'm really struggling and could use a better system.
Any advice, help, or just pointing me in a better direction would be really appreciated.
Thanks.
Depending on your client (eg, I use SequelPro on a Mac), you might be able to import CSVs. This is generally pretty shaky, but you can also export your Excel document as a CSV... how convenient.
However, this doesn't really help with your database structure. Granted, using foreign keys is a good idea, but importing that data unobtrusively (and easily) is something that will need to likely be done a row at a time.
However, you could try modifying something like this to suit your needs, by first exporting your Excel document as a CSV, removing the header row (the first one), and then using regular expressions on it to change it into a big chunk of SQL. For example:
Your CSV:
myval1.1,myval1.2,myval1.3,myval1.4
myval2.1,myval2.2,myval2.3,myval2.4
...
At which point, you could do something like:
myCsvText.replace(/^(.+),(.+),(.+)$/mg, 'INSERT INTO table_name(col1, col2, col3) VALUES($1, $2, $3)')
where you know the number of columns, their names, and how their values are organized (via the regular expression & replacement).
Might be a good place to start.
Your table looks OK. Since you have a variable number of fields, it seems logical to expand vertically. Although you might want to make it easier on yourself by changing DataFileID and FieldID into FieldName and DataFileName, unless you will use them in a lot of other tables too.
Getting data from Excel into SQL Server is unfortunately not so easy as you would expect from two Microsoft products interacting with eachother. There are several routes that I know of that you can take:
Work with CSV files instead of Excel files. Excel can edit CSV files just as easily as Excel files, but CSV is an infinitely more reliable datasource when it comes to importing. You don't get problems with different file formats for different Excel versions, Excel having to be installed on the computer that will run the script or quirks with automatic datatype recognition. A CSV can be read with the BCP commandline tool, the BULK INSERT command or with SSIS. Then use stored procedures to convert the data from a horizontal bulk of columns into a pure vertical format.
Use SSIS to read the data directly from the Excel file(s). It is possible to make a package that loops over several Excel files. A drawback is that the column format and the sheet name of the Excel file has to be known beforehand, and so a different template (with a separate loop) has to be made each time a new Excel format arrives. There exist third-party SSIS components that claim to be more flexible, but I haven't tested them out yet.
Write a Visual C# program or PowerShell script that grabs the Excel file, extracts the data and outputs into your SQL table. Visual C# is a pretty easy language with powerful interfaces into Office and SQL Server. I don't know how big the learning curve is to get started, but once you do, it will be a pretty easy program to write. I have also heard good things about Powershell.
Create an Excel Macro that uses VB code to open other Excel files, loop through their data and write the results either in a predefined sheet or as CSV to disk. Once everything is in a standard format it will be easy to import the data using one of the above methods.
Since I have had headaches with 1) and 2) before, I would advise on either 3) or 4). Because of my greater experience with VBA than Visual C# or Powershell, I´d go for 4) if I was in a hurry. But I think 3) is the better investment for the long term.
(You could also go adventurous and use another script language, such as Python as I once did because Python is cool, unfortunately Python offers pretty slow and limited interfaces to SQL server and Excel)
Good luck!
I am looking for a tool that can serialize and/or transform SQL Result Sets into XML. Getting dumbed down XML generation from SQL result sets is simple and trivial, but that's not what I need.
The solution has to be database neutral, and accepts only regular SQL query results (no db xml support used). A particular challenge of this tool is to provide nested XML matching any schema from row based results. Intermediate steps are too slow and wasteful - this needs to happen in one single step; no RS->object->XML, preferably no RS->XML->XSLT->XML. It must support streaming due to large result sets, big XML.
Anything out there for this?
With SQL Server you really should consider using the FOR XML construct in the query.
If you're using .Net, just use a DataAdapter to fill a dataset. Once it's in a dataset, just use its .WriteXML() method. That breaks your DB->object->XML rule, but it's really how things are done. You might be able to work something out with a datareader, but I doubt it.
Not that I know of. I would just roll my own. It's not that hard to do, maybe something like this:
#!/usr/bin/env jruby
import java.sql.DriverManager
# TODO some magic to load the driver
conn = DriverManager.getConnection(ARGV[0], ARGV[1], ARGV[2])
res = conn.executeQuery ARGV[3]
puts "<result>"
meta = res.meta_data
while res.next
puts "<row>"
for n in 1..meta.column_count
column = meta.getColumnName n
puts "<#{column}>#{res.getString(n)}</#{column}"
end
puts "</row>"
end
puts "</result>"
Disclaimer: I just made all of that up, I'm not even bothering to pretend that it works. :-)
In .NET you can fill a dataset from any source and then it can write that out to disk for you as XML with or without the schema. I can't say what performance for large sets would be like. Simple :)
Another option, depending on how many schemas you need to output, and/or how dynamic this solution is supposed to be, would be to actually write the XML directly from the SQL statement, as in the following simple example...
SELECT
'<Record>' ||
'<name>' || name || '</name>' ||
'<address>' || address || '</address>' ||
'</Record>'
FROM
contacts
You would have to prepend and append the document element, but I think this example is easy enough to understand.
dbunit (www.dbunit.org) does go from sql to xml and vice versa; you might be able to modify it more for your needs.
Technically, converting a result set to an XML file is straight forward and doesn't need any tool unless you have a requirement to convert the data structure to fit specific export schema. In general the result set gets the top-level element of an XML file, then you produce a number of record elements containing attributes, which effectively are the fields of a record.
When it comes to Java, for example, you just need appropriate JDBC driver for interfacing with DBMS of your choice addressing the database independency requirement (usually provided by a DBMS vendor), and a few lines of code to read a result set and print out an XML string per record, per field. Not a difficult task for an average Java developer in my opinion.
Anyway, the more concrete purpose you state the more concrete answer you get.
In Java, you may just fill an object with the xml data (like an entity bean) and then use XMLEncoder to get it to xml. From there you may use XSLT for further conversion or XMLDecoder to bring it back to an object.
Greetz, GHad
PS: See http://ghads.wordpress.com/2008/09/16/java-to-xml-to-java/ for an example for the Object to XML part... From DB to Object multiple more way are possible: JDBC, Groovy DataSets or GORM. Apache Common Beans may help to fill up JavaBeans via Reflection-like methods.
I created a solution to this problem by using the equivalent of a mail merge using the resultset as the source, and a template through which it was merged to produce the desired XML.
The template was standard XML, with a Header element, a Footer element and a Body element. Using a CDATA block in the Body element allowed me to include a complete XML structure that acted as the template for each row. In order to include a fields from the resultset in the template, I used markers that looked like this <[FieldName]>. The template was then pre-parsed to isolate the markers such that in operation, the template requests each of the fields from the resultset as the Body is being produced.
The Header and Footer elements are output only once at the beginning and end of the output set. The body could be any XML or text structure desired. In your case, it sounds like you might have several templates, one for each of your desired schemas.
All of the above was encapsulated in a Template class, such that after loading the Template, I merely called merge() on the template passing the resultset in as a parameter.