I have been testing neo4j for graph projects for 1 or 2 month now and it has been really efficient, but I'm having a hard time finding how to solve one of my problem and I'm seeking for advice.
I'm using neo4j to store graph databases and check that they follow some structural requirements, for example, I have a db modeling dependency between items : the nodes are the items and the links are labeled "need" or "incompatible" to model the dependency and I want neo4j to check the coherence of the data.
I coded the checker in a server plugin and it works very well. But now I would like to allow users to connect to the database, modify the data (without saving the modification yet), check that the modifications are not breaking the coherence and then save the modifications.
I found the http endpoint which can keep a transaction open and it completely fits the "modifying the db without saving" need, but I can't find how to run my checker on the modified data : is there a way to run something else than Cypher query with the http endpoint or do I have to consider an other way to solve this ?
I now it would be possible to run my checker using the TransactionEventHandler beforeCommit, but it means the user couldn't know if his data are okay without starting a commit, and the fact that the data are split between the db without modification and the TransactionData which store the modification make the checker tricky to apply.
So, if someone knows how I could solve this, it would be great.
Thank you.
Your options is to use Unmanaged Extension and Transaction Event API.
You are able to handle incoming transaction and read all data which are in it. If transaction break your rules, then you can discard the transaction.
I recommend you to use GraphAware framework for that.
Here is the great article about that http://graphaware.com/neo4j/transactions/2014/07/11/neo4j-transaction-event-api.html
I have a little bit of logs [ 200Mbytes/per day ]. What I want is to use certain data from this logs to build some statistics and show it through web interface. After pre-processing these files I get 4-5 files like this one:
hadooper#ubuntu:/usr/local/hadoop$ du -h part-r-00000
4.0K part-r-00000
hadooper#ubuntu:/usr/local/hadoop$ cat part-r-00000
201508042015 444335775
201508042020 563
201508042025 320787123
.....
I'm planning to store all this at least for year, maybe even more. Not sure yet.
My question is where would be better to store and retrieve data: files or database ?
I'm planning to use rails as backend. And as for now it seems like storing everything in files are ok option. But there might be some drawbacks in long term which I'm not aware of right now.
I'm sure there are a lot of experienced people who solved similar tasks. Would much appreciate your thoughts and help
If you are only trying to store the files, store as flat/zipped file or add to the database and then export them as backup file from the database. Preparing backup from database will ensure easier import later when you need the data.
If you will need to perform queries on them too all this time, store them in database as querying to database is faster (because of indices) and easier (because of availability of DDL, DML etc.)
If you are worried about security, encrypt your files or encrypt the database and then export.
Let me know if there is some case I forgot to address.
I need to insert 800000 records into an MS Access table. I am using Delphi 2007 and the TAdoXxxx components. The table contains some integer fields, one float field and one text field with only one character. There is a primary key on one of the integer fields (which is not autoinc) and two indexes on another integer and the float field.
Inserting the data using AdoTable.AppendRecord(...) takes > 10 Minutes which is not acceptable since this is done every time the user starts using a new database with the program. I cannot prefill the table because the data comes from another database (which is not accessible through ADO).
I managed to get down to around 1 minute by writing the records to a tab separated text file and using a tAdoCommand object to execute
insert into table (...) select * from [filename.txt] in "c:\somedir" "Text;HDR=Yes"
But I don't like the overhead of this.
There must be a better way, I think.
EDIT:
Some additional information:
MS Access was chosen because it does not need any additional installation on the target machine(s) and the whole database is contained in one file which can be easily copied.
This is a single user application.
The data will be inserted only once and will not change for the lifetime of the database. Though, the table contains one additional field that is used as a flag to indicate that the corresponding record in another database has been processed by the user.
One minute is acceptable (up to 3 minutes would be too) and my solution works, but it seems too complicated to me, so I thought there should be an easier way to do this.
Once the data has been inserted, the performance of the table is quite good.
When I started planning/implementing the feature of the program working with the Access database the table was not required. It only became necessary later on, when another feature was requested by the customer. (Isn't that always the case?)
EDIT:
From all the answers I got so far, it seems that I already got the fastest method for inserting that much data into an Access table. Thanks to everybody, I appreciate your help.
Since you've said that the 800K records data won't change for the life of the database, I'd suggest linking to the text file as a table, and skip the insert altogether.
If you insist on pulling it into the database, then 800,000 records in 1 minute is over 13,000 / second. I don't think you're gonna beat that in MS Access.
If you want it to be more responsive for the user, then you might want to consider loading some minimal set of data, and setting up a background thread to load the rest while they work.
It would be quicker without the indexes. Can you add them after the import?
There are a number of suggestions that may be of interest in this thread Slow MSAccess disk writing
What about skipping the text file and using ODBC or OLEDB to import directly from the source table? That would mean altering your FROM clause to use the source table name and an appropriate connect string as the IN '' part of the FROM clause.
EDIT:
Actually I see you say the original format is xBase, so it should be possible to use the xBase ISAM that is part of Jet instead of needing ODBC or OLEDB. That would look something like this:
INSERT INTO table (...)
SELECT *
FROM tablename IN 'c:\somedir\'[dBase 5.0;HDR=NO;IMEX=2;];
You might have to tweak that -- I just grabbed the connect string for a linked table pointing at a DBF file, so the parameters might be slightly different.
Your text based solution seems the fastest, but you can get it quicker if you could get an preallocated MS Access in a size near the end one. You can do that by filling an typical user database, closing the application (so the buffers are flushed) and doing a manual deletion of all records of that big table - but not shrinking/compacting it.
So, use that file to start the real filling - Access will not request any (or very few) additional disk space. Don't remeber if MS Access have a way to automate this, but it can help much...
How about an alternate arrangement...
Would it be an option to make a copy of an existing Access database file that has this table you need and then just delete all the other data in there besides this one large table (don't know if Access has an equivalent to something like "truncate table" in SQL server)?
I would replace MS Access with another database, and for your situation I see Sqlite is the best choice, it doesn't require any installation into client machine, and it's very fast database and one of the best embedded database solution.
You can use it in Delphi in two ways:
You can download the Database engine Dll from Sqlite website and use Free Delphi component to access it like Delphi SQLite components or SQLite4Delphi
Use DISQLite3 which have the engine built in, and you don't have to distribute the dll with your application, they have a free version ;-)
if you still need to use MS Access, try to use TAdoCommand with SQL Insert statment directly instead of using TADOTable, that should be faster than using TADOTable.Append;
You won't be importing 800,000 records in less than a minute, as someone mentioned; that's really fast already.
You can skip the annoying translate-to-text-file step however if you use the right method (DAO recordsets) for doing the inserts. See a previous question I asked and had answered on StackOverflow: MS Access: Why is ADODB.Recordset.BatchUpdate so much slower than Application.ImportXML?
Don't use INSERT INTO even with DAO; it's slow. Don't use ADO either; it's slow. But DAO + Delphi + Recordsets + instantiating the DbEngine COM object directly (instead of via the Access.Application object) will give you lots of speed.
You're looking in the right direction in one way. Using a single statement to bulk insert will be faster than trying to iterate through the data and insert it row by row. Access, being a file-based database will be exceedingly slow in iterative writes.
The problem is that Access is handling how it optimizes writes internally and there's not really any way to control it. You've probably reached the maximum efficiency of an INSERT statement. For additional speed, you should probably evaluate if there's any way around writing 800,000 records to the database every time you start the application.
Get SQL Server Express (free) and connect to it from Access an external table. SQL express is much faster than MS Access.
I would prefill the database, and hand them the file itself, rather than filling an existing (but empty) database.
If the data you have to fill changes, then keep an ODBC access database (MDB file) synchronized on the server using a bit of code to see changes in the main database and copy them to the access database.
When the user requests a new database zip up the MDB, transfer it to them, and open it.
Alternately, you may be able to find code that opens and inserts data into databases directly.
Alternately, alternately, you may be able to find another format (other than csv) which access can import that is faster.
-Adam
Also check to see how long it takes to copy the file. That will be the lower bound of how fast you can write data. In db's like SQL, it usually takes a bulk load utility to get close to that speed. As far as I know, MS never created a tool to write directly to MS Access tables the way bcp does. Specialized ETL tools will also optimize some of the steps surrounding the insert, such as the way SSIS does transformations in memory, DTS likewise has some optimizations.
Perhaps you could open a ADO Recordset to the table with lock mode adLockBatchOptimistic and CursorLocation adUseClient, write all the data to the recordset, then do a batch update (rs.UpdateBatch).
If it's coming from dbase, can you just copy the data and index files and attach directly without loading? Should be pretty efficient (from the people who bring you FoxPro.) I imagine it would use the existing indexes too.
At the least, it should be a pretty efficient single-command Import.
how much do the 800,000 records change from one creation to the next? Would it be possible to pre populate the records and then just update the ones that have changed in the external database when creating the new database?
This may allow you to create the new database file quicker.
How fast is your disk turning? If it's 7200RPM, then 800,000 rows in 3 minutes is still 37 rows per disk revolution. I don't think you're going to do much better than that.
Meanwhile, if the goal is to streamline the process, how about a table link?
You say you can't access the source database via ADO. Can you set up a table link in MS Access to a table or view in the source database? Then a simple append query from the table link would copy the data over from the source database to the target database for you. I'm not sure, but I think this would be pretty fast.
If you can't set up a table link until runtime, maybe you could build the table link programatically via ADO, then build the append query programatically, then invoke the append query.
HI
The best way is Bulk Insert from txt File as they said
you should insert your record's in txt file then bulk insert the txt file into table
that time should be less than 3 second.
If I have large number of files (n x 100K individual files) what would be most efficient way to store them in iOS file system (from speed of access to the file by path point of view)? Should I dump them all in single folder or break them in multilevel folder hierarchy.
Basically this breaks in three questions:
does file access time depend on number of "sibling" files (I think
answer is yes. If I am correct file names are organized into b-tree
so it should be O(log n))?
how expensive is traversing from one folder to another along the
path (is it something like m * O( log nm ) - where m is number of
components in the path and nm is number of "siblings" at each path
component )?
What gets cached at file system level to make above assumptions incorrect?
It would be great if some one had direct experience with this kind of problem and can share some real life results.
You comments will be highly appreciated
This seems like it might provide relevant, hard data:
File System vs Core Data: the image cache test
http://biasedbit.com/blog/filesystem-vs-coredata-image-cache
Conclusion:
File system cache is, as expected, faster. Core Data falls shortly behind when storing (marginally slower) but load times are way higher when performing single random accesses.
For such a simple case Core Data functionality really doesn't pay up, so stick to the file system version.
I think you should store everything is a one folder and create a hash table which include key (file name) and value (source path) pare.By creating hash table complexity with be constant log(1) and this will speed up your process as well.
The file system is not an optimal database. With that many thousands of files, you should consider using Core Data, or other database instead to store the name and contents of each file.
I am working on a content management application in which the data being stored on the database is extremely generic. In this particular instance a container has many resources and those resources map to some kind of digital asset, whether that be a picture, a movie, an uploaded file or even plain text.
I have been arguing with a colleague for a week now because in addition to storing the pictures, etc - they would like to store the text assets on the file system and have the application look up the file location(from the database) and read in the text file(from the file system) before serving to the client application.
Common sense seemed to scream at me that this was ridiculous and if we are bothering to look up something from the database, we might as well store the text in a database column and have it served along up with the row lookup. Database lookup + File IO seemed sounds uncontrollably slower then just Database Lookup. After going back and forth for some time, I decided to run some benchmarks and found the results a little surprising. There seems to be very little consistency when it comes to benchmark times. The only clear winner in the benchmarks was pulling a large dataset from the database and iterating over the results to display the text asset, however pulling objects one at a time from the database and displaying their text content seems to be neck and neck.
Now I know the limitations of running benchmarks, and I am not sure I am even running the correct idea of "tests" (for example, File system writes are ridiculously faster then database writes, didn't know that!). I guess my question is for confirmation. Is File I/O comparable to database text storage/lookup? Am I missing a part of the argument here? Thanks ahead of time for your opinions/advice!
A quick work about what I am using:
This is a Ruby on Rails application,
using Ruby 1.8.6 and Sqlite3. I plan
on moving the same codebase to MySQL
tomorrow and see if the benchmarks are
the same.
The major advantage you'll get from not using the filesystem is that the database will manage concurrent access properly.
Let's say 2 processes need to modify the same text as the same time, synchronisation with the filesystem may lead to race conditions, whereas you will have no problem at all with everyhing in database.
I think your benchmark results will depend on how you store the text data in your database.
If you store it as LOB then behind the scenes it is stored in an ordinary file.
With any kind of LOB you pay the Database lookup + File IO anyway.
VARCHAR is stored in the tablespace
Ordinary text data types (VARCHAR et al) are very limited in size in typical relational database systems. Something like 2000 or 4000 (Oracle) sometimes 8000 or even 65536 characters. Some databases support long text
but these have serious drawbacks and are not recommended.
LOBs are references to file system objects
If your text is larger you have to use a LOB data type (e.g. CLOB in Oracle).
LOBs usually work like this:
The database stores only a reference to a file system object.
The file system object contains the data (e.g. the text data).
This is very similar to what your colleague proposes except the DBMS lifts the heavy work of
managing references and files.
The bottom line is:
If you can store your text in a VARCHAR then go for it.
If you can't you have two options: Use a LOB or store the data in a file referenced from the database. Both are technically similar and slower than using VARCHAR.
I did this before. Its a mess, you need to keep the filesystem and the database synchronized all the time, so that makes the programming more complicated, as you would guess.
My advice is either go for an all filesystem solution, or all database solution, depending on the data. Notably, if you require lots of searches, conditional data retrieval, then go for database, otherwise fs.
Note that database may not be optimized for storage of large binary files. Still, remember, if you use both, youre gonna have to keep them synchronized, and it doesnt make for an elegant nor enjoyble (to program) solution.
Good luck!
At least, if your problems come from the "performance side", you could use a "no SQL" storage solution like Redis (via Ohm, for example), or CouchDB...