Data sources cover the result set of SQL queries or stored procedures, and
the 2D table from the text or Excel files. Owing to the technical competence
or versioning, various reporting tools may only support a single data source,
such as JasperReport, Quiee, BIRT, and Crystal Report.
With years of experience, I've concluded several methods to share and discuss
Virtual Data Source for JasperReport Commercial Server
The Virtual Data Source provided in the JasperReport business edition can
solve this problem. With wizard, one virtual table can be created by joining
two entity tables of either physical table or SQL. The interface is shown
esProc for reporting tools
Unlike the bundled reporting tools, esProc is a data source development tool
that is totally independent of databases and reporting tools.
Data Sources Join for BIRT
BIRT is the famous open ... (more)
The MapReduce of Hadoop is a widely-used parallel computing framework.
However, its code reuse mechanism is inconvenient, and it is quite cumbersome
to pass parameters. Far different from our usual experience of calling the
library function easily, I found both the coder and the caller must bear a
sizable amount of precautions in mind when writing even a short pieces of
program for calling by others.
However, we finally find that esProc could easily realize code reuse in
hadoop. Still a simple and understandable example of grouping and
summarizing, let's check out a solution with... (more)
Enterprises always have various data sources, for instance, CRM system may
use SQL Server, sales reports adopt Excel, ERP applies Oracle database. When
it comes to actual business analysis, enterprises usually need to conduct
interactive computation, including filter, group, etc among various data
environments. But data Interaction between multiple data sources are not easy
to realize with some traditional statistical computing tools. In order to
solve such kind of problems, esProc which adapts to various data environments
comes into being.
Support of various data sources is an... (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)
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)