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Tag - array binding

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2014, Tuesday November 18

HTTP remote access for SynDB SQL execution

For mORMot, we developed a fully feature direct access layer to any RDBMS, implemented in the SynDB.pas unit.

You can use those SynDB classes to execute any SQL statement, without any link to the framework ORM.
At reading, the resulting performance is much higher than using the standard TDataSet component, which is in fact a true performance bottleneck.
It has genuine features, like column access via late-binding, an innovative ISQLDBRows interface, and ability to directly access the low-level binary buffers of the database clients.

We just added a nice feature to those classes: the ability to access remotely, via plain HTTP, to any SynDB supported database!

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2014, Monday March 3

ORM enhanced for BATCH insert

We just committed some nice features to the ORM kernel, and SynDB* classes of our mORMot framework.

During BATCH insertion, the ORM is able to generate some optimized SQL statements, depending on the target database, to send several rows of data at once.
It induces a noticeable speed increase when saving several objects into an external database.

This feature is available for SQlite3 (3.7.11 and later), MySQL, PostgreSQL, MS SQL Server (2008 and up), Oracle, Firebird and NexusDB.
Since it is working at SQL level, it is available for all supported access libraries, e.g. ODBC, OleDB, Zeos/ZDBC, UniDAC, FireDAC.
It means that even properties not implementing array binding (like OleDB, Zeos or UniDAC) are able to have a huge boost at data insertion, ready to compete with the (until now) more optimized libraries.

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2013, Monday January 28

External database speed improvements

Some major speed improvements have been made to our SynDB* units, and how they are used within the mORMot persistence layer.
It results in an amazing speed increase, in some cases.

Here are some of the optimizations how took place in the source code trunk:

Overall, I observed from x2 to x10 performance boost with simple Add() operations, using ODBC, OleDB and direct Oracle access, when compare to previous benchmarks (which were already impressive).
BATCH mode performance is less impacted, since it by-passed some of those limitations, but even in this operation mode, there is some benefits (especially with ODBC and OleDB).

Here are some results, directly generated by the supplied "15 - External DB performance" sample.

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2012, Monday December 31

Enhance existing projects with mORMot

Even if mORMot will be more easily used in a project designed from scratch, it fits very well the purpose of evolving any existing Delphi project, or even creating the server side part of an AJAX application. 

One benefit of such a framework is to facilitate the transition from a Client-Server architecture to a N-Tier layered pattern.

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2012, Sunday October 28

SynDBOracle: Open Source native Oracle access

(this is an update of the article published in 2011/07)

For our mORMot framework, and in completion to our SynOleDB unit, we added a new Open Source unit, named SynDBOracle. It allows direct access to any remote Oracle server, using the Oracle Call Interface.

Oracle Call Interface (OCI) is the most comprehensive, high performance, native unmanaged interface to the Oracle Database that exposes the full power of the Oracle Database. We wrote a direct call of the oci.dll library, using our DB abstraction classes introduced for SynOleDB.

We tried to implement all best-practice patterns detailed in the official Building High Performance Drivers for Oracle document

Resulting speed is quite impressive: for all requests, SynDBOracle is 3 to 5 times faster than a SynOleDB connection using the native OleDB Provider supplied by Oracle. We noted also that our implementation is 10 times faster than the one provided with ZEOS/ZDBC, which is far from optimized.

You can use the latest version of the Oracle Instant Client provided by Oracle - see this link - which allows you to run your applications without installing the standard (huge) Oracle client or having an ORACLE_HOME. Just deliver the dll files in the same directory than your application, and it will work.

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2012, Friday September 14

Updated mORMot benchmarks on another HW configuration

With a refreshed hardware, and the latest code modifications of the framework code, I run again the benchmark sample.

The new PC has an Intel Core i7-2600 CPU, running on Windows Seven 64-bit, with anti-virus (Norton) fully enabled.
Oracle 11g database is remotely accessed over a corporate network, so latency and bandwidth is not optimal.
Still no SSD, but a standard 7200 rpm hard drive of 500 GB.

The results are impressive, when compared to the previous run using a Core 2 Duo CPU - mORMot's optimized code achieves amazing speed on this platform.
And I guess the 8MB of L3 cache of the Core i7 does wonders with our code.

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2012, Wednesday July 25

Synopse mORMot benchmark

After having tested and enhanced the external database speed (including BATCH mode), we are now able to benchmark all database engines available in mORMot.

In fact, the ORM part of our framework has several potential database backends, in addition to the default SQLite3 file-based engine.
Each engine may have its own purpose, according to the application expectation.

The following tables try to sum up all available possibilities, and give some benchmark (average rows/seconds for writing or read). 

In these tables:

  • 'internal' means use of the internal SQLite3 engine;
  • 'external' stands for an external access via SynDB;
  • 'TObjectList' indicates a TSQLRestServerStaticInMemory instance either static (with no SQL support) or virtual (i.e. SQL featured via SQLite3 virtual table mechanism) which may persist the data on disk as JSON or compressed binary;
  • 'trans' stands for Transaction, i.e. when the write process is nested within BeginTransaction / Commit calls;
  • 'batch' mode will be described in this article;
  • 'read one' states that one object is read per call (ORM generates a SELECT * FROM table WHERE ID=?);
  • 'read all' is when all 5000 objects are read in a single call (i.e. running SELECT * FROM table);
  • ACID is an acronym for "Atomicity Consistency Isolation Durability" properties, which guarantee that database transactions are processed reliably: for instance, in case of a power loss or hardware failure, the data will be saved on disk in a consistent way, with no potential loss of data.
In short: depending on the database you can persist up to 150,000 objects per second, or retrieve  240,000 objects per second.
With a high-performance database like Oracle and our direct access classes, you write 53,000 and read 72,000 objects per second.
Difficult to find a faster ORM, I suspect. :)

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2012, Thursday July 19

Oracle Array Binding and BATCH performance

A common issue with Client-Server databases is the latency introduced for each query.

For example, suppose you have a requirement to first collect some information from your application’s users and then insert that information into a table in Oracle Database.

The first obvious option is to insert these multiple rows into the table through a loop in your program. This loop iterates over the data to be inserted and does what is known as a single-row insert , because the application sends one single row of data to the database at a time. Due to the network latency (typically around 1 ms over a corporate network), it would achieve not more than 500-600 requests per second to let the work done, since for each INSERT, a so-called round-trip occurs: a message is sent to Oracle, then a response is sent back to the client.

You have another option for inserting multiple rows of data into the table— that reduces the number of round-trips and improves application performance, database performance, and network resource use. Rather than having the application send a single row of data to the database at a time, it can use array binding to send the data in batches of rows. Therefore, you reduce a lot the number of round-trips to be processed, and enhance performance by a factor of about 100.

Our SynDB unit has been enhanced to introduce new TSQLDBStatement.BindArray() methods, introducing array binding for faster database batch modifications (only implemented in SynDBOracle by now - but MS SQL has a similar feature called OleDB bulk insert).
It is available from the ORM side or mORMot, when working with external tables, in BATCH mode.

Thanks to this enhancement, inserting records within Oracle comes from 400-500 rows per second to more than 50000 rows per second!
It was also a good opportunity to speed up the BATCH process globally, and to benchmark our Oracle back-end against existing external databases, i.e. SQLite3 (as file or in-memory), and Jet / MS Access / .mdb engine.

Note that this article scope is only about virtual tables linked to external databases (i.e. TSQLRecordExternal). Plain TSQLRecord classes will access directly to the SQLite3 engine or in-memory TList, so speed will be even higher than the below values.

Featuring benchmark source code and nice performance charts.

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