Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: MapReduce and parallel DBMSs: friends or foes?
Parallel database systems: the future of high performance database systems
LIBRA: Lightweight Data Skew Mitigation in MapReduce
The family of mapreduce and large-scale data processing systems
Distributed Relational Database Performance In Cloud Computing: An Investigative Study
System Level Concurrency Control for Distributed Database Systems
Fragmentation Design for Efficient Query Execution over Sensitive Distributed Databases
Designing good algorithms for MapReduce and beyond
Automating physical database design in a parallel database
A transputer T9000 family based architecture for parallel database machines
MapReduce across Distributed Clusters for Data-intensive Applications
Benchmarking Replication and Consistency Strategies in Cloud Serving Databases: HBase and Cassandra
Improving MapReduce Performance in Heterogeneous Environments
A simulation approach to evaluating design decisions in MapReduce setups
Schism: a Workload-Driven Approach to Database Replication and Partitioning
Optimistic Concurrency Control in Geographically Distributed Databases for Concurrent OLTP Transactions
Piccolo: Building Fast, Distributed Programs with Partitioned Tables
Hardware-Oblivious Parallelism for In-Memory Column-Stores
Speedy transactions in multicore in-memory databases
Using SQL primitives and parallel DB servers to speed up knowledge discovery in large relational databases.
Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads
Topic classification and clustering on Indonesian complaint tweets for bandung government using supervised and unsupervised learning
Large-scale characterization of Mandarin pronunciation errors made by native speakers of European languages.
Answer Passage Retrieval for Question Answering
the emerging transactive microgrid controller : illustrating its concept , functionality , and business case .
SCOPE: easy and efficient parallel processing of massive data sets