Random access with a distributed Bitmap Join Index for Star Joins.

Indices improve the performance of relational databases, especially on queries that return a small portion of the data (i.e., low-selectivity queries). Star joins are particularly expensive operations that commonly rely on indices for improved performance at scale. The development and support of index-based solutions for Star Joins are still at very early stages. To address this gap, we propose a distributed Bitmap Join Index (dBJI) and a framework-agnostic strategy to solve join predicates in linear time. For empirical analysis, we used common Hadoop technologies (e.g., HBase and Spark) to show that dBJI significantly outperforms full scan approaches by a factor between 59% and 88% in queries with low selectivity from the Star Schema Benchmark (SSB). Thus, distributed indices may significantly enhance low-selectivity query performance even in very large databases.

FESTIval: A versatile framework for conducting experimental evaluations of spatial indices.

The use of a spatial index is a common strategy to improve the performance of spatial queries in spatial database systems and Geographic Information Systems. Choosing the right spatial index to be employed in a given context requires a quantitative method to analyze the performance of spatial indices. This is done through extensive experimental evaluations. However, conducting these evaluations is an expensive, error-prone, and challenging task because (i) spatial objects are complex data to manage, (ii) spatial indices can apply different parameter values and thus assume distinct configurations, and (iii) there are indices specifically developed for different storage systems, such as disks and flash memories. In this article, we propose FESTIval, a versatile framework for conducting experimental evaluations of spatial indices. FESTIval has the following main advantages: •the support for different types of disk-based and flash-aware spatial indices;•the specification and execution of user-defined workloads;•the use of a data schema that stores index configurations and statistical data of executed workloads. Because of its characteristics, FESTIval allows users to reproduce executed experiments. Further, FESTIval provides an extensible environment, where any spatial dataset can be handled by spatial indices. FESTIval has been used to validate new proposals of flash-aware spatial indices, such as eFIND-based indices.

Genome of Herbaspirillum seropedicae strain SmR1, a specialized diazotrophic endophyte of tropical grasses.

The molecular mechanisms of plant recognition, colonization, and nutrient exchange between diazotrophic endophytes and plants are scarcely known. Herbaspirillum seropedicae is an endophytic bacterium capable of colonizing intercellular spaces of grasses such as rice and sugar cane. The genome of H. seropedicae strain SmR1 was sequenced and annotated by The Paraná State Genome Programme--GENOPAR. The genome is composed of a circular chromosome of 5,513,887 bp and contains a total of 4,804 genes. The genome sequence revealed that H. seropedicae is a highly versatile microorganism with capacity to metabolize a wide range of carbon and nitrogen sources and with possession of four distinct terminal oxidases. The genome contains a multitude of protein secretion systems, including type I, type II, type III, type V, and type VI secretion systems, and type IV pili, suggesting a high potential to interact with host plants. H. seropedicae is able to synthesize indole acetic acid as reflected by the four IAA biosynthetic pathways present. A gene coding for ACC deaminase, which may be involved in modulating the associated plant ethylene-signaling pathway, is also present. Genes for hemagglutinins/hemolysins/adhesins were found and may play a role in plant cell surface adhesion. These features may endow H. seropedicae with the ability to establish an endophytic life-style in a large number of plant species.