The big data phenomenon is becoming a fact. L'augmentation continue de la numérisation et de la connexion des appareils à Internet est la création de solutions et de services courants intelligents, riches et plus personnalisés. The emergence of the NoSQL databases, like Cassandra, with their massive scalability and high availability encourages us to investigate the management of the stored data within such storage system. In our present work, we harness the geohashing technique to enable spatial queries as extension to Cassandra query language capabilities while preserving the native syntax. The developed framework showed the feasibility of this approach where basic spatial queries are underpinned and the query response time is reduced by up to 70 times for a fairly large area.

The big data phenomenon is becoming a fact. Continuous increase of digitization and connecting devices to the Internet are making current solutions and services smarter, richer and more personalized. The emergence of the NoSQL databases, like Cassandra, with their massive scalability and high availability encourages us to investigate the management of the stored data within such storage system. In our present work, we harness the geohashing technique to enable spatial queries as extension to Cassandra query language capabilities while preserving the native syntax. The developed framework showed the feasibility of this approach where basic spatial queries are underpinned and the query response time is reduced by up to 70 times for a fairly large area.

The big data phenomenon is becoming a fact. Continuous increase of digitization and connecting devices to Internet are making current solutions and services smarter, richer and more personalized. The emergence of the NoSQL databases, like Cassandra, with their massive scalability and high availability encourages us to investigate the management of the stored data within such storage system. In our present work, we harness the geohashing technique to enable spatial queries as extension to Cassandra query language capabilities while preserving the native syntax. The developed framework showed the feasibility of this approach where basic spatial queries are underpinned and the query response time is reduced by up to 70 times for a fairly large area.

The big data phenomenon is becoming a fact. Continuous increase of digitization and connecting devices to Internet are making current solutions and services smarter, richer and more personalized. The emergence of the NoSQL databases, like Cassandra, with their massive scalability and high availability encourages us to investigate the management of the stored data within such storage system. In our present work, we harness the geohashing technique to enable spatial queries as extension to Cassandra query language capabilities while preserving the native syntax. The developed framework showed the feasibility of this approach where basic spatial queries are underpinned and the query response time is reduced by up to 70 times for a fairly large area.

أصبحت ظاهرة البيانات الضخمة حقيقة واقعة. تؤدي الزيادة المستمرة في الرقمنة وتوصيل الأجهزة بالإنترنت إلى جعل الحلول والخدمات الحالية أكثر ذكاءً وثراءً وتخصيصًا. إن ظهور قواعد بيانات NoSQL، مثل كاساندرا، بقابليتها الهائلة للتطوير وتوافرها العالي يشجعنا على التحقيق في إدارة البيانات المخزنة داخل نظام التخزين هذا. في عملنا الحالي، نقوم بتسخير تقنية الجيوهاشينغ لتمكين الاستعلامات المكانية كامتداد لقدرات لغة الاستعلام كاساندرا مع الحفاظ على بناء الجملة الأصلي. أظهر الإطار المطور جدوى هذا النهج حيث يتم دعم الاستعلامات المكانية الأساسية ويتم تقليل وقت الاستجابة للاستعلام بما يصل إلى 70 مرة لمنطقة كبيرة إلى حد ما.