Related papers: A Storage Advisor for Hybrid-Store Databases
We study the problem of optimizing data storage and access costs on the cloud while ensuring that the desired performance or latency is unaffected. We first propose an optimizer that optimizes the data placement tier (on the cloud) and the…
In this paper, we present MorphStore, an open-source in-memory columnar analytical query engine with a novel holistic compression-enabled processing model. Basically, compression using lightweight integer compression algorithms already…
Hybrid cloud provides an attractive solution to microservices for better resource elasticity. A subset of application components can be offloaded from the on-premises cluster to the cloud, where they can readily access additional resources.…
Relational databases play a central role in many information systems. Their schema contains structural (e.g. tables and columns) and behavioral (e.g. stored procedures or views) entity descriptions. Then, just like for ``normal'' software,…
Modern Internet applications often produce a large volume of user activity records. Data analysts are interested in cohort analysis, or finding unusual user behavioral trends, in these large tables of activity records. In a traditional…
The enormous quantity of data produced every day together with advances in data analytics has led to a proliferation of data management and analysis systems. Typically, these systems are built around highly specialized monolithic operators…
Storage and memory systems for modern data analytics are heavily layered, managing shared persistent data, cached data, and non-shared execution data in separate systems such as distributed file system like HDFS, in-memory file system like…
Large-scale storage cluster systems need to manage a vast amount of data locations. A naive data locations management maintains pairs of data ID and nodes storing the data in tables. However, it is not practical when the number of pairs is…
Arguably data is the new natural resource in the enterprise world with an unprecedented degree of proliferation. But to derive real-time actionable insights from the data, it is important to bridge the gap between managing the data that is…
Modern high-performance computing (HPC) environments rely on hybrid storage systems (HSS) that combine multiple storage devices with diverse latency, bandwidth, endurance, and capacity characteristics to meet the performance, capacity, and…
Indexes are critical for efficient data retrieval and updates in modern databases. Recent advances in machine learning have led to the development of learned indexes, which model the cumulative distribution function of data to predict…
Data compression schemes have exhibited their importance in column databases by contributing to the high-performance OLAP (Online Analytical Processing) query processing. Existing works mainly concentrate on evaluating compression schemes…
Modern analytical workloads increasingly combine relational data with array-valued attributes. While columnar database systems efficiently process such workloads, their ability to optimize queries that interleave relational operators with…
Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express a wide range of physical database layouts, going well beyond the row- and…
The proliferation of location-based services has led to massive spatial data generation. Spatial join is a crucial database operation that identifies pairs of objects from two spatial datasets based on spatial relationships. Due to the…
It is very challenging part to keep safely all required data that are needed in many applications for user in cloud. Storing our data in cloud may not be fully trustworthy. Since client doesn't have copy of all stored data, he has to depend…
The existing resource allocation policy for application instances in Kubernetes cannot dynamically adjust according to the requirement of business, which would cause an enormous waste of resources during fluctuations. Moreover, the…
Recommenders take place on a wide scale of e-commerce systems, reducing the problem of information overload. The most common approach is to choose a recommender used by the system to make predictions. However, users vary from each other;…
In-memory (transactional) data stores are recognized as a first-class data management technology for cloud platforms, thanks to their ability to match the elasticity requirements imposed by the pay-as-you-go cost model. On the other hand,…
Multi-tenancy hosting of users in cloud NoSQL data stores is favored by cloud providers because it enables resource sharing at low operating cost. Multi-tenancy takes several forms depending on whether the back-end file system is a local…