BI meet Big Data, a Happy Story

Cada vez esta más cerca poder hacer análisis BI OLAP tradicionales sobre entornos Big Data, gracias a Kylin. Hace unas semanas, lo comentábamos en esta entrada , en donde también mostrábamos ejemplos reales de vistas OLAP y Dashboards en funcionamiento.

Ahora, os actualizamos con información reciente de los programadores de Kylin ( inglés )

What is Apache Kylin?

Kylin is an OLAP engine on Hadoop. As shown in Figure 1, Kylin sits on top of Hadoop and exposes relational data to upper applications via the standard SQL interface.
Kylin can handle big data sets and is fast in terms of query latency, which differentiates it from other SQL on Hadoop. For example, the biggest instance of Kylin in production that we’re aware of is at toutiao.com, a news feed app in China. This app has a table of three trillion rows and the average query response time is less than one second. We’ll discuss what makes Kylin so fast in the next section.
Another feature of the Kylin engine is that it can support complex data models. For example, there is a 60-dimension model running at CPIC, an insurance group in China. Kylin provides standard JDBC / ODBC / RestAPI interfaces, enabling a connection with any SQL application.

Kyligence has also developed an online demo , showcasing the BI experience on 100 million airline records. Check it out to learn, for example, the most delayed airline to San Francisco International Airport in the past 20 years. (Login with username “analyst”, password “analyst”, select the “airline_cube”, drag and drop dimensions and measures to play with the data set.)

Cuando se busca una camiseta de club, es útil comparar medidas, corte y detalles de confección antes de decidir. Para ordenar la búsqueda, equipacion de futbol del Liverpool puede revisarse junto con las medidas y el tipo de ajuste preferido. También conviene revisar las condiciones descritas para evitar confundir estilo, talla y comodidad.