There are always needs to build E-commerce sites with Credit Card transactions securely and seamlessly. In Singapore market, eNETs is the most well-known company providing payment gateway services. Up to now, eNETS only provide API for .NET and Java platform. In this post, I will show you my solution to integrate eNETS and Ruby on Rails via Java. Steps: 1. Build JAR file to submit payment info to eNETS, i named it enets.jar. This jar file will return output from eNETS to console in text format. I attached sample program built with NetBean, you can download it here: eNETS. After downloading, you just copy that folder to your NetBean projects folder as shown in below image. 2. Follow eNETS guideline, change setting for java security as well as generate merchant.priv.pgp.asc, merchant.pub.pgp.asc. 3. Change config: log4j.properties, NETSConfig.xml 4. Build enets.jar file from source files in NetBean. Right click on project root, Clean and Build. 5. Generate command to execute enets.jar, something like this: “java -jar #{RAILS_ROOT}/vendor/extensions/payment_gateway/lib/enets/eNETS.jar #{mid} #{tid} #{paymentMode} #{amt} #{currency} #{merRef} #{submitMode} #{merCertId} #{pan} #{expiry} #{stan} #{paymentType} #{successURL} #{successURLParams} #{failureURL} #{failureURLParams} #{notify_url} #{notify_url_params} #{name} #{cvv} #{post_url} #{post_url_params} #{cancel_url} #{cancel_url_params} #{bill_first_name} #{bill_last_name} #{bill_initial} #{bill_addr1} #{bill_addr2} #{bill_coy_name} #{bill_city} #{bill_state} #{bill_zip_code} #{bill_country} #{bill_mobile_num} #{bill_phone_num} #{bill_fax_num} #{bill_email} #{ship_first_name} #{ship_last_name} #{ship_initial} #{ship_addr1} #{ship_addr2} #{ship_coy_name} #{ship_city} #{ship_state} #{ship_zip_code} #{ship_country} #{ship_mobile_num} #{ship_phone_num} #{ship_fax_num} #{ship_email} #{shopper_ip_addr} #{product_format} #{product_details} #{gw_url}” 6. Run enets.jar from ruby console with output = %x[#{command}]. %x[] command will store output to output variable for later processing. It is not the same as system() or exec() ruby command. Read more on Jay Fields’ blog: Ruby Kernel system, exec and %x 7. Parse results returned...
Scott: As you mentioned, there is an Apache version of Hadoop and then there’s the Cloudera version. As different companies wrap themselves around different open source projects, they’re structured in different ways. Talk a little bit about Cloudera and what you add to the public open source version of Hadoop, in terms of additional software, support, or services. Amr: I should start by saying that Cloudera is an enterprise software company. Open source is an enabler for us, and it’s part of what we do, but our mission is about building enterprise software for large-scale data processing in internal or external clouds. via...
The group at Yahoo! that I came from was using Hadoop for data analytics and data warehousing. We had something like 100,000 web servers across the world, and once we collected data from across all these servers, we dumped it into Hadoop, which became the place where we stored all of the data, instead of traditional network storage. Our reasoning for doing that was a matter of economics, given the quantity of hardware. Hadoop lets us scalably process that data, clean it up, and normalize it so we could pass it along to the systems that need it. Hadoop is getting very wide adoption in the data warehousing and business intelligence domains. One of the biggest uses within Yahoo! right now is dealing with all of the log information from servers. Analyzing that information allows for better spam filtering, ad targeting, content targeting, A/B testing for new features, et cetera. It’s not web-specific. For example, everybody does data warehousing, and we see very strong adoption there. Separate from that, your example of oil companies is a very good one, as is the financial sector. Right now, we do have a couple of very large financial institutions working with us on these exact problems, taking huge amounts of data from domains like credit card processing and building predictive models for fraud that enable better decisions, for example, about whether to block or allow a given transaction. In the stock market, Hadoop is being used to do simulations that help predict option pricing and related problems. That’s another very healthy market that we’ve seen growth in. via howsoftwareisbuilt.com Knowing that Yahoo...
First, it’s worth making the important clarifying point that Hadoop is not a database. Hadoop is a data processing system, and in fact, I would even go as far as saying Hadoop is an operating system. The core of an operating system boils down to a file system, the storage of files, and a process scheduling system that runs applications on top of these files. There are many other components that help with devices, credentials and user access, and so on, but that is the core. Hadoop is exactly the same thing. The core of Hadoop is the Hadoop Distributed File System, which is a file system that’s runs across many nodes. It links together the file systems on many local nodes to make them into one big file system. Hadoop MapReduce is really the job scheduling system that takes care of scheduling jobs on top of all those nodes. That is the key distinction between Hadoop’s approach and that of database systems. Hadoop, at its heart, does not require any structure to your data. You can just upload files directly from anywhere, like a web server, RFID device, or cell phone mobile device, directly into Hadoop. They could be images, videos, or just a bunch of bits. They don’t have to have a schema with column types and so on, which gives you tremendous agility and flexibility. Hadoop has a very nice model that I sometimes refer to as schema on read. Whereas defining your schema as you’re writing the data in limits what you can put in by requiring it to be conformant to the schema that...
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