390 research outputs found
MonetDB/DataCell: Online Analytics in a Streaming Column-Store
In DataCell, we design streaming functionalities in a mod- ern relational database kernel which targets big data analyt- ics. This includes exploitation of both its storage/execution engine and its optimizer infrastructure. We investigate the opportunities and challenges that arise with such a direction and we show that it carries significant advantages for mod- ern applications in need for online analytics such as web logs, network monitoring and scientific data management. The major challenge then becomes the efficient support for specialized stream features, e.g., multi-query processing and incremental window-based processing as well as exploiting standard DBMS functionalities in a streaming environment such as indexing.
In this demo, we present the DataCell system, an exten- sion of the MonetDB open-source column-store for online an- alytics. The demo gives the user the opportunity to experi- ence the features of DataCell such as processing both stream and persistent data and performing window based process- ing. The demo provides a visual interface to monitor the critical system components, e.g., how query plans transform from typical DBMS query plans to online query plans, how data flows through the query plans as the streams evolve, how DataCell maintains intermediate results in columnar form to avoid repeated evaluation of the same stream por- tions, etc. The demo also provides the ability to interac- tively set the test scenarios regarding input data and various DataCell knobs
Enhanced Stream Processing in a DBMS Kernel
Continuous query processing has emerged as a promising query processing paradigm with numerous applications. A recent development is the need to handle both streaming queries and typical one-time queries in the same application. For example, data warehousing can greatly benefit from the integration of stream semantics, i.e., online analysis of incoming data and combination with existing data. This is especially useful to provide low latency in data-intensive analysis in big data warehouses that are augmented with new data on a daily basis.
However, state-of-the-art database technology cannot handle streams efficiently due to their "continuous" nature. At the same time, state-of-the-art stream technology is purely focused on stream applications. The research efforts are mostly geared towards the creation of specialized stream management systems built with a different philosophy than a DBMS. The drawback of this approach is the limited opportunities to exploit successful past data processing technology, e.g., query optimization techniques.
For this new problem we need to combine the best of both worlds. Here we take a completely different route by designing a stream engine on top of an existing relational database kernel. This includes reuse of both its storage/execution engine and its optimizer infrastructure. The major challenge then becomes the efficient support for specialized stream features. This paper focuses on incremental window-based processing, arguably the most crucial stream-specific requirement. In order to maintain and reuse the generic storage and execution model of the DBMS, we elevate the problem at the query plan level. Proper op
Quality predictors of abdominal fetal electrocardiography recording in antenatal ambulatory and bedside settings
Background: Fetal electrocardiography using an abdominal monitor (Monica AN24β’) could increase the diagnostic use of fetal heart rate (fHR) variability measurements. However, signal quality may depend on factors such as maternal physical activity, posture, and bedside versus ambulatory setting. Methods: Sixty-three healthy women wore the monitor at home and 42 women during a hospital stay. All women underwent a posture experiment, and all home and 13 hospital participants wore the monitor during daytime and nighttime. The success rate (SR) of fHR detection was analyzed in relation to maternal physical activity, posture, daytime versus nighttime, and other maternal and fetal predictors. Results: Ambulatorily, the SR was 86.8% for nighttime and 40.2% for daytime. The low daytime SR was largely due to effects of maternal physical activity and posture. The in-hospital SR was lower during nighttime (71.1%) and similar during daytime (43.3%). SR was related to gestational age, but not affected by pre-pregnancy and current body mass index or fetal growth restriction. Conclusions: The success of beat-to-beat fHR detection strongly depends on the home/hospital setting and predictors such as time of recording, activity levels, and maternal posture. Its clinical utility may be limited in periods of unsupervised recording with physical activity or posture shifts
ΠΠ΄Π½ΠΎΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ½ΡΠΉ ΠΌΠΈΠΊΡΠΎΠΌΠ΅Ρ Π°Π½ΠΈΡΠ΅ΡΠΊΠΈΠΉ Π³ΠΈΡΠΎΡΠΊΠΎΠΏ Ρ ΡΠ°ΡΡΠΈΡΠ΅Π½Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΎΡΠΎΠΉ ΠΏΡΠΎΠΏΡΡΠΊΠ°Π½ΠΈΡ
ΠΠ±ΡΠ΅ΠΊΡΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΌΠΈΠΊΡΠΎΠΌΠ΅Ρ
Π°Π½ΠΈΡΠ΅ΡΠΊΠΈΠΉ Π³ΠΈΡΠΎΡΠΊΠΎΠΏ, Ρ ΡΠ°ΡΡΠΈΡΠ΅Π½Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΎΡΠΎΠΉ ΠΏΡΠΎΠΏΡΡΠΊΠ°Π½ΠΈΡ.
Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ β ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΎΠ΄Π½ΠΎΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡΠΎΠΌΠ΅Ρ
Π°Π½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π³ΠΈΡΠΎΡΠΊΠΎΠΏΠ°, Ρ ΡΠ°ΡΡΠΈΡΠ΅Π½Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΎΡΠΎΠΉ ΠΏΡΠΎΠΏΡΡΠΊΠ°Π½ΠΈΡ.
Π ΠΏΡΠΎΡΠ΅ΡΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»Π°ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΉ ΡΡ
Π΅ΠΌΡ ΠΈ ΡΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π³ΠΈΡΠΎΡΠΊΠΎΠΏΠ°, ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΡΡ ΡΠ°ΡΡΠΎΡΠ½ΡΠΉ ΠΈ ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ, ΡΠ°ΡΡΠ΅Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ², ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ Π²ΠΎΠΏΡΠΎΡΡ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠ³ΠΎ ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½ΡΠ°.
ΠΠ±Π»Π°ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ: Π°Π²ΡΠΎΠΌΠΎΠ±ΠΈΠ»ΡΠ½Π°Ρ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΡ.The object of research is a micromechanical gyroscope, with extended bandwidth.
The purpose of research - development of a single-component micromechanical gyroscope, with extended bandwidth.
The study was carried out to provide a functional circuit and making a mathematical model of the gyroscope, as frequency and static design analysis, the calculation of basic parameters, the issues of technology, social responsibility and financial management.
Applications: Automotive industry
Column-store support for RDF data management: not all swans are white
This paper reports on the results of an independent evaluation of the
techniques presented in the VLDB 2007 paper "Scalable Semantic Web Data
Management Using Vertical Partitioning", authored by D. Abadi, A. Marcus, S.
R. Madden, and K. Hollenbach. We revisit the proposed benchmark and examine
both the data and query space coverage. The benchmark is extended to cover a
larger portion of the query space in a canonical way. Repeatability of the
experiments is assessed using the code base obtained from the authors.
Inspired by the proposed vertically-partitioned storage solution for RDF
data and the performance figures using a column-store, we conduct a
complementary analy- sis of state-of-the-art RDF storage solutions. To this
end, we employ MonetDB/SQL, a fully-functional open source column-store, and
a well-known --- for its performance --- commercial row-store DBMS.We
implement two relational RDF storage solutions β triple-store and
vertically-partitioned --- in both systems. This allows us to expand the
scope of with the performance characterization along both dimensions ---
triple-store vs. vertically-partitioned and row-store vs. column-store ---
individually, before analyzing their combined effects. A detailed report of
the experimental test-bed, as well as an in-depth analysis of the parameters
involved, clarify the scope of the solution originally presented and
position the results in a broader context by covering more systems
ΠΠ°ΠΌΠ΅Π½Π° ΡΠ»Π΅ΠΊΡΡΠΎΠ΄Π²ΠΈΠ³Π°ΡΠ΅Π»Ρ ΠΠΠ ΡΡΡΠ±ΠΎΠΏΡΠΈΠ²ΠΎΠ΄ΠΎΠΌ Π½Π° ΠΠ΅ΠΌΠ΅ΡΠΎΠ²ΡΠΊΠΎΠΉ Π’ΠΠ¦
Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ Π·Π°ΠΌΠ΅Π½Ρ ΡΠ»Π΅ΠΊΡΡΠΎΠ΄Π²ΠΈΠ³Π°ΡΠ΅Π»Ρ ΠΠΠ ΡΡΡΠ±ΠΎΠΏΡΠΈΠ²ΠΎΠ΄ΠΎΠΌ Π½Π° ΠΠ΅ΠΌΠ΅ΡΠΎΠ²ΡΠΊΠΎΠΉ Π’ΠΠ¦, Ρ ΡΡΡΠ°Π½ΠΎΠ²ΠΊΠΎΠΉ ΡΡΡΠ±ΠΎΠΏΡΠΈΠ²ΠΎΠ΄Π° Π½Π° ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠΉ ΡΡΠ½Π΄Π°ΠΌΠ΅Π½Ρ. Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΠ΅Π½ΠΊΠ° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΠΎΡΠΏΡΡΠΊΠ° ΡΠ»Π΅ΠΊΡΡΠΎΡΠ½Π΅ΡΠ³ΠΈΠΈ ΠΎΡ ΡΡΠ°Π½ΡΠΈΠΈ Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ Π·Π°ΡΡΠ°Ρ Π½Π° ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΡΠ΅ Π½ΡΠΆΠ΄Ρ ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ ΠΌΠ°Π½Π΅Π²ΡΠ΅Π½Π½ΠΎΡΡΠΈ Π’ΠΠ¦.In this paper we consider the possibility of replacing the turbine drive motor PEN to Kemerovo CHP , with the installation of turbine drive on the existing foundation. The aim is to assess the possibility of increasing the supply of electric power from the plant by reducing the costs of their own needs and improving maneuverability CHP
ΠΠΎΠ΄Π±ΠΎΡ ΠΌΠ΅Ρ Π°Π½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π±ΠΎΡΡΠ±Ρ Ρ Π°ΡΡΠ°Π»ΡΡΠΎΠ²ΠΎ-ΠΏΠ°ΡΠ°ΡΠΈΠ½ΠΎΠ²ΡΠΌΠΈ ΠΎΡΠ»ΠΎΠΆΠ΅Π½ΠΈΡΠΌΠΈ
Π Π΄ΠΈΠΏΠ»ΠΎΠΌΠ½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΡΠΏΠΎΡΠΎΠ±Ρ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΠΏΠ°ΡΠ°ΡΠΈΠ½Π°, ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΠΠ‘ΠΠ, ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΡΠΏΠΎΡΠΎΠ±Ρ Π±ΠΎΡΡΠ±Ρ Ρ ΠΎΡΠ»ΠΎΠΆΠ΅Π½ΠΈΡΠΌΠΈ, ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ ΠΏΠ°ΡΠ΅Π½ΡΠ½ΡΠΉ ΠΏΠΎΠΈΡΠΊ.
ΠΡΠΈΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π² Π΄ΠΈΠΏΠ»ΠΎΠΌΠ½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠ΅Ρ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ, ΡΡΠΎ Π΄Π»Ρ Π΄Π°Π½Π½ΠΎΠΉ ΡΠΊΠ²Π°ΠΆΠΈΠ½Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠΊΡΠ΅Π±ΠΊΠΎΠ² β ΡΠ΅Π½ΡΡΠ°ΡΠΎΡΠΎΠ² ΡΠ΅Π»Π΅ΡΠΎΠΎΠ±ΡΠ°Π·Π½ΠΎ, ΡΡΠ»ΠΎΠ²ΠΈΠ΅ ΠΏΡΠΎΡΠ½ΠΎΡΡΠΈ Π²ΡΠΏΠΎΠ»Π½ΡΠ΅ΡΡΡ.
Π Π΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠΉ Π΄ΠΈΠΏΠ»ΠΎΠΌΠ½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°ΡΡΠ΅Ρ Π½Π° ΠΏΡΠΎΡΠ½ΠΎΡΡΡ ΡΡΠ°Π½Π³ Π¨Π‘ΠΠ£. Π ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½ΠΎ, ΠΊΠ°ΠΊ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ ΡΠΊΠ²Π°ΠΆΠΈΠ½Ρ Π²Π»ΠΈΡΡΡ Π½Π° Π²ΡΠΏΠ°Π΄Π΅Π½ΠΈΠ΅ ΠΏΠ°ΡΠ°ΡΠΈΠ½Π° ΠΈΠ· Π½Π΅ΡΡΠΈ.In the thesis work the methods of paraffin deposition, mechanisms of AFS, modern ways of dealing with deposits, also held a patent search.
Powered by a research paper calculation shows that for this well use scrapers - centralizers appropriate strength condition is satisfied.
The result of conducted research paper is to calculate the strength SHSNU rods. The paper considers how well the parameters affect the loss of paraffin oil
Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΌΠΎΠ΄ΡΠ»ΡΡΠΎΡΠ° Π΄Π»Ρ Π±ΠΈΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»Π°Π·Π΅ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΎΠ½ΠΈΡΠΎΡΠ°
Phase II study of continuous daily sunitinib dosing in patients with previously treated advanced non-small cell lung cancer
Background:Sunitinib malate (SUTENT) has promising single-agent activity given on Schedule 4/2 (4 weeks on treatment followed by 2 weeks off treatment) in advanced non-small cell lung cancer (NSCLC).Methods:We examined the activity of sunitinib on a continuous daily dosing (CDD) schedule in an open-label, multicentre phase II study in patients with previously treated, advanced NSCLC. Patients β©Ύ18 years with stage IIIB/IV NSCLC after failure with platinum-based chemotherapy, received sunitinib 37.5βmg per day. The primary end point was objective response rate (ORR). Secondary end points included progression-free survival (PFS), overall survival (OS), 1-year survival rate, and safety.Results:Of 47 patients receiving sunitinib, one patient achieved a confirmed partial response (ORR 2.1% (95% confidence interval (CI) 0.1, 11.3)) and 11 (23.4%) had stable disease (SD) β©Ύ8 weeks. Five patients had SD>6 months. Median PFS was 11.9 weeks (95% CI 8.6, 14.1) and median OS was 37.1 weeks (95% CI 31.1, 69.7). The 1-year survival probability was 38.4% (95% CI 24.2, 52.5). Treatment was generally well tolerated.Conclusions:The safety profile and time-to-event analyses, albeit relatively low response rate of 2%, suggest single-agent sunitinib on a CDD schedule may be a potential therapeutic agent for patients with advanced, refractory NSCLC
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics (Extended Version)
There has been significant amount of excitement and recent work on GPU-based
database systems. Previous work has claimed that these systems can perform
orders of magnitude better than CPU-based database systems on analytical
workloads such as those found in decision support and business intelligence
applications. A hardware expert would view these claims with suspicion. Given
the general notion that database operators are memory-bandwidth bound, one
would expect the maximum gain to be roughly equal to the ratio of the memory
bandwidth of GPU to that of CPU. In this paper, we adopt a model-based approach
to understand when and why the performance gains of running queries on GPUs vs
on CPUs vary from the bandwidth ratio (which is roughly 16x on modern
hardware). We propose Crystal, a library of parallel routines that can be
combined together to run full SQL queries on a GPU with minimal materialization
overhead. We implement individual query operators to show that while the
speedups for selection, projection, and sorts are near the bandwidth ratio,
joins
achieve less speedup due to differences in hardware capabilities.
Interestingly, we show on a popular analytical workload that full query
performance gain from running on GPU exceeds the bandwidth ratio despite
individual operators having speedup less than bandwidth ratio, as a result of
limitations of vectorizing chained operators on CPUs, resulting in a 25x
speedup for GPUs over CPUs on the benchmark
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