In Java development, we may encounter the complex set operations. Java alone
is not powerful enough to save programmers' efforts in implementing the
computation details, which is time-consuming and poor in code reuse. In view
of this, programmers usually resort to dynamic calculation script for set
SQL is surely the first kind of script that comes into most programmers'
mind. However, to their disappointments, SQL does not support the explicit
set, and is unable to represent the sets of a set, ordered set, generic set,
and only the result set can be recognized as a set. Therefore, it is only the
subset of the true set. Many operations on sets are hard to implement through
SQL. Moreover, the computation is not limited on database, such as the data
from Excel and even there is no database in the application environment. In
this case, the usage of SQL databa... (more)
In report development, we may need to present the data from multiple
databases in one report, such as data from MSSQL database for CRM and Oracle
database for ERP. If the reporting tool like iReport only supports single
data source, then we need to consolidate the multiple data sources into a
single data source.
The Crystal, BIRT, and other so-called reporting tools for multiple data
source can only join 2 result sets roughly, and are also very inconvenient
for the complex multi-data-source computations. For example, compute the
yearly growth rate of order value for each client i... (more)
Recently, I read "Why Big Data Projects Fail" by Stephen Brobst. I can’t
agree more with his opinions which exposed the problem I’ve been worried
about. In this article, I am going to further discuss this topic to remind
the enterprises to beware of falling into such pitfall of failure.
Let’s have a look on a positive example. As a successful enterprise in
leveraging big data, how does Google make use of the big data?
1. Collect the row data, capture the contents of each website, e-mail, or
Cookie, and extract the key information.
2. Create the complex syndetic index for this inf... (more)
The data computation layer in between the data persistent layer and the
application layer is responsible for computing the data from data persistence
layer, and returning the result to the application layer. The data
computation layer of Java aims to reduce the coupling between these two
layers and shift the computational workload from them. The typical
computation layer is characterized with below features:
Ability to compute on the data from arbitrary data persistence layers, not
only databases, but also the non-database Excel, Txt, or XML files. Of all
these computations, the... (more)
The Big Data Real-time Application is a scenario to return the computation
and analysis results in real time even if there are huge amounts of data.
This is an emerging demand on database applications in recent years.
In the past, because there wasn't a lot of data, the computation was simple,
and few parallelisms, the pressure on the database wasn't great. A high-end
or middle-range database server or cluster could allocate enough resources to
meet the demand. Moreover, in order to rapidly and parallel access to the
current business data and the historic data, users also tended t... (more)