Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Streaming Analytics on Large-scale Oceanographic Data using
  Apache Spark   Real-world data from diverse domains require real-time scalable analysis.
Large-scale data processing frameworks or engines such as Hadoop fall short
when results are needed on-the-fly. Apache Spark's streaming library is
increasingly becoming a popular choice as it can stream and analyze a
significant amount of data. In this paper, we analyze large-scale geo-temporal
data collected from the USGODAE (United States Global Ocean Data Assimilation
Experiment) data catalog, and showcase and assess the ability of Spark stream
processing. We measure the latency of streaming and monitor scalability by
adding and removing nodes in the middle of a streaming job. We also verify the
fault tolerance by stopping nodes in the middle of a job and making sure that
the job is rescheduled and completed on other nodes. We design a full-stack
application that automates data collection, data processing and visualizing the
results. We also use Google Maps API to visualize results by color coding the
world map with values from various analytics.

24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat