At present ring slub carded yarn is very popular to produce value added product for ornamentation purpose in the apparel industry. During spinning different parameters influenced the spinning performance. The main aim...At present ring slub carded yarn is very popular to produce value added product for ornamentation purpose in the apparel industry. During spinning different parameters influenced the spinning performance. The main aim of this study was to investigate the effect of spindle speed as well as traveller weight on yarn quality. The Ne 28, Ne 30 and Ne 34 carded slub yarns were produced at the spindle speed of 15,500 rpm, 16,000 rpm, 16,500 rpm, 17,000 rpm and 17,500 rpm on the ring frame with using traveller number 3/0, 4/0, 5/0 and 6/0. The yarn properties like mass variation percentage (CVm%), unevenness (U%), hairiness, yarn breakage rate, yarn imperfection were investigated. It was found that traveller number 5/0 showed lower Um%, CVm% for Ne 28 and Ne 30 carded slub yarn compared to traveller number 3/0 and 4/0. On the other hand traveller number 6/0 showed better Um%, CVm%, thin places (-50%)/km and end breakage% for Ne 34 carded slub yarn compared to traveller number 4/0 and 5/0. It was also observed that increasing end breakage rate as the spindle speed of ring frame was increased.展开更多
Generally, ring spun yarns are manufactured from roving which is produced by roving frame. In this paper, an experiment has been done producing ring spun cotton yarn directly from finisher drawn sliver eliminatin...Generally, ring spun yarns are manufactured from roving which is produced by roving frame. In this paper, an experiment has been done producing ring spun cotton yarn directly from finisher drawn sliver eliminating the roving frame. Total 3 types of yarn with the various linear density of 8 Ne, 10 Ne & 12 Ne were produced using a roving frame and without using a roving frame. In the next step, physical and mechanical properties of those yarns including unevenness, imperfections, hairiness & tenacity were investigated. The result showed that ring spun cotton yarns produced from sliver exhibited inferior physical and mechanical properties compared with samples from the conventional ring spinning system.展开更多
Artificial yarn muscles show great potential in applications requiring low-energy consumption while maintaining high performance. However, conventional designs have been limited by weak ion-yarn muscle interactions an...Artificial yarn muscles show great potential in applications requiring low-energy consumption while maintaining high performance. However, conventional designs have been limited by weak ion-yarn muscle interactions and inefficient “rocking-chair” ion migration. To address these limitations, we present an electrochemical artificial yarn muscle design driven by a dual-ion co-regulation system. By utilizing two reaction channels, this system shortens ion migration pathways, leading to faster and more efficient actuation. During the charging/discharging process, PF_6~- ions react with carbon nanotube yarn, while Li~+ ions react with an Al foil. The intercalation reaction between PF_6~- and collapsed carbon nanotubes allows the yarn muscle to achieve an energy-free high-tension catch state. The dual-ion coordinated yarn muscles exhibit superior contractile stroke, maximum contractile rate, and maximum power densities, exceeding those of “rocking-chair” type ion migration yarn muscles. The dual-ion co-regulation system enhances the ion migration rate during actuation, resulting in improved performance. Moreover, the yarn muscles can withstand high levels of isometric stress, displaying a stress of 61 times that of skeletal muscles and 8 times that of “rocking-chair” type yarn muscles at higher frequencies. This technology holds significant potential for various applications, including prosthetics and robotics.展开更多
The blending of different fibers is done for the manufacturing of yarn to ensure the presence of multiple properties in the resultant yarn which is impossible if we use only one type of fiber. Tencel is regenerated ce...The blending of different fibers is done for the manufacturing of yarn to ensure the presence of multiple properties in the resultant yarn which is impossible if we use only one type of fiber. Tencel is regenerated cellulosic fiber & flax is natural bast fiber. Tencel shows more versatility than flax. Tencel has a softer feel with a variety of end uses. Tencel is wrinkle-prone and stiff. Tencel shows extreme strength even in wet conditions and at the same time, it is more durable than linen. The most important fact is that the heat dissipation property of flax is 5 times higher than wool & 19 times higher than silk. Linen clothing can lower the body temperature by 3 to 4 degree celsius in hot weather than clothing made of wool and silk. A yarn made of both Tencel & linen (50:50) will contain the properties of both fibers. At the same time, we can make this yarn more aesthetic by incorporating a slub. It was observed that the slub yarn made by blending Tencel and flax fiber shows better properties than the slub yarn of the same count made from the blending of cotton and flax.展开更多
Tailoring water supply to achieve confined heating has proven to be an effective strategy for boosting solar interfacial evaporation rates.However,because of salt clogging during desalination,a critical point of const...Tailoring water supply to achieve confined heating has proven to be an effective strategy for boosting solar interfacial evaporation rates.However,because of salt clogging during desalination,a critical point of constriction occurs when controlling the water rate for confined heating.In this study,we demonstrate a facile and scalable weaving technique for fabricating core-sheath photothermal yarns that facilitate controlled water supply for stable and efficient interracial solar desalination.The core-sheath yarn comprises modal fibers as the core and carbon fibers as the sheaths.Because of the core-sheath design,remarkable liquid pumping can be enabled in the carbon fiber bundle of the dispersed superhydrophilic modal fibers.Our woven fabrics absorb a high proportion(92%)of the electromagnetic radiation in the solar spectrum because of the weaving structure and the carbon fiber sheath.Under one-sun(1 kW·m^(-2))illumination,our woven fabric device can achieve the highest evaporation rate(of 2.12kg·m^(-2)·h^(-1) with energy conversion efficiency:93.7%)by regulating the number of core-sheath yarns.Practical application tests demonstrate that our device can maintain high and stable desalination performance in a 5 wt%NaCl solution.展开更多
In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBo...In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.展开更多
A new algorithm of measurement slub yarn parameter was put forward to improve precision and efficient. The basic principal of measurement slub yarn by parallel-plate capacitor was introduced,and slub yarns were tested...A new algorithm of measurement slub yarn parameter was put forward to improve precision and efficient. The basic principal of measurement slub yarn by parallel-plate capacitor was introduced,and slub yarns were tested with a measurement system developed by ourselves. Time sequence for slub length and slub space can be got. And distributions of slub length,slub space and slub scaling factor can also be obtained. The agreement can be attained compared with those original settings. Some error was analyzed also. Consequently this system is effective,and can be adopted in practice.展开更多
Jamdani weaving is one of the oldest heredities of Bangladesh. From the beginning 100% cotton yarn was used to produce high quality jamdani saree. The weavers were the finest with weaving skills. Higher yarn count yar...Jamdani weaving is one of the oldest heredities of Bangladesh. From the beginning 100% cotton yarn was used to produce high quality jamdani saree. The weavers were the finest with weaving skills. Higher yarn count yarns were used to weave the jamdani saree. In course of time at present manmade fibres are also used to produce jamdani saree. The use of filament yarn may have eased the manufacturing difficulties, but the jamdani saree is missing its originality without 100% cotton. In this project, random jamdani saree sample was collected to identify the fibre composition. Samples of filament were also collected from the manufacturer and tested. It was evident that instead of cotton yarn in warp and weft silk and polyester filament yarn were used.展开更多
Results The population had large variations for lint yield,fibre properties,predicted yarn properties,and composite fibre quality values.Lint yield with all fibre quality traits was not correlated.When the selection w...Results The population had large variations for lint yield,fibre properties,predicted yarn properties,and composite fibre quality values.Lint yield with all fibre quality traits was not correlated.When the selection was conducted first to keep those with improved fibre quality,and followed for high yields,a large proportion in the resultant populations was the same between selections based on Cottonspec predicted yarn quality and HVI-measured fibre properties.They both exceeded the selection based on FQI and Background The approach of directly testing yarn quality to define fibre quality breeding objectives and progress the selection is attractive but difficult when considering the need for time and labour.The question remains whether yarn prediction tools from textile research can serve as an alternative.In this study,using a dataset from three seasons of field testing recombinant inbred line population,Cottonspec,a software developed by the Commonwealth Scientific and Industrial Research Organisation(CSIRO)for predicting ring spun yarn quality from fibre properties measured by High Volume Instrument(HVI),was used to select improved fibre quality and lint yield in the population.The population was derived from an advanced generation inter-crossing of four CSIRO conventional commercial varieties.The Cottonspec program was able to provide an integrated index of the fibre qualities affecting yarn properties.That was compared with selection based on HVI-measured fibre properties,and two composite fibre quality variables,namely,fibre quality index(FQI),and premium and discount(PD)points.The latter represents the net points of fibre length,strength,and micronaire based on the Premiums and Discounts Schedule used in the market while modified by the inclusion of elongation.PD points.Conclusions The population contained elite segregants with improved yield and fibre properties,and Cottonspec predicted yarn quality is useful to effectively capture these elites.There is a need to further develop yarn quality prediction tools through collaborative efforts with textile mills,to draw better connectedness between fibre and yarn quality.This connection will support the entire cotton value chain research and evolution.展开更多
In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space...In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.展开更多
The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs.This paper has proposed a novel scheduler for enhancement of the perfo...The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs.This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator(YARN)scheduler,called the Adaptive Node and Container Aware Scheduler(ANACRAC),that aligns cluster resources to the demands of the applications in the real world.The approach performs to leverage the user-provided configurations as a unique design to apportion nodes,or containers within the nodes,to application thresholds.Additionally,it provides the flexibility to the applications for selecting and choosing which node’s resources they want to manage and adds limits to prevent threshold breaches by adding additional jobs as needed.Node or container awareness can be utilized individually or in combination to increase efficiency.On top of this,the resource availability within the node and containers can also be investigated.This paper also focuses on the elasticity of the containers and self-adaptiveness depending on the job type.The results proved that 15%–20%performance improvement was achieved compared with the node and container awareness feature of the ANACRAC.It has been validated that this ANACRAC scheduler demonstrates a 70%–90%performance improvement compared with the default Fair scheduler.Experimental results also demonstrated the success of the enhancement and a performance improvement in the range of 60%to 200%when applications were connected with external interfaces and high workloads.展开更多
针对电信大数据处理系统中存在的问题,文章提出一种基于Spark on Yarn模型的SY-TPP。在SY-TPP平台上,应用Hadoop2.0 Yarn标准,并利用Spark分布式存储技术,将SY-TPP系统的数据在内存中进行集中处理。以分级聚类算法为案例,对SY-TPP平台...针对电信大数据处理系统中存在的问题,文章提出一种基于Spark on Yarn模型的SY-TPP。在SY-TPP平台上,应用Hadoop2.0 Yarn标准,并利用Spark分布式存储技术,将SY-TPP系统的数据在内存中进行集中处理。以分级聚类算法为案例,对SY-TPP平台的开发过程进行了详细的分析。实验结果表明,TPP平台上的GB级用户可以在半个工作日内完成数据处理,而32个实体节点的SYTPP系统的速度比相同配置下的Map Reduce平台提高了10.25倍。展开更多
文摘At present ring slub carded yarn is very popular to produce value added product for ornamentation purpose in the apparel industry. During spinning different parameters influenced the spinning performance. The main aim of this study was to investigate the effect of spindle speed as well as traveller weight on yarn quality. The Ne 28, Ne 30 and Ne 34 carded slub yarns were produced at the spindle speed of 15,500 rpm, 16,000 rpm, 16,500 rpm, 17,000 rpm and 17,500 rpm on the ring frame with using traveller number 3/0, 4/0, 5/0 and 6/0. The yarn properties like mass variation percentage (CVm%), unevenness (U%), hairiness, yarn breakage rate, yarn imperfection were investigated. It was found that traveller number 5/0 showed lower Um%, CVm% for Ne 28 and Ne 30 carded slub yarn compared to traveller number 3/0 and 4/0. On the other hand traveller number 6/0 showed better Um%, CVm%, thin places (-50%)/km and end breakage% for Ne 34 carded slub yarn compared to traveller number 4/0 and 5/0. It was also observed that increasing end breakage rate as the spindle speed of ring frame was increased.
文摘Generally, ring spun yarns are manufactured from roving which is produced by roving frame. In this paper, an experiment has been done producing ring spun cotton yarn directly from finisher drawn sliver eliminating the roving frame. Total 3 types of yarn with the various linear density of 8 Ne, 10 Ne & 12 Ne were produced using a roving frame and without using a roving frame. In the next step, physical and mechanical properties of those yarns including unevenness, imperfections, hairiness & tenacity were investigated. The result showed that ring spun cotton yarns produced from sliver exhibited inferior physical and mechanical properties compared with samples from the conventional ring spinning system.
基金financial support obtained from the National Key Research and Development Program of China (2020YFB1312900)the National Natural Science Foundation of China (21975281)+1 种基金Key Research Project of Zhejiang lab (No. K2022NB0AC04)Jiangxi Double Thousand Talent Program (No. jxsq2020101008)。
文摘Artificial yarn muscles show great potential in applications requiring low-energy consumption while maintaining high performance. However, conventional designs have been limited by weak ion-yarn muscle interactions and inefficient “rocking-chair” ion migration. To address these limitations, we present an electrochemical artificial yarn muscle design driven by a dual-ion co-regulation system. By utilizing two reaction channels, this system shortens ion migration pathways, leading to faster and more efficient actuation. During the charging/discharging process, PF_6~- ions react with carbon nanotube yarn, while Li~+ ions react with an Al foil. The intercalation reaction between PF_6~- and collapsed carbon nanotubes allows the yarn muscle to achieve an energy-free high-tension catch state. The dual-ion coordinated yarn muscles exhibit superior contractile stroke, maximum contractile rate, and maximum power densities, exceeding those of “rocking-chair” type ion migration yarn muscles. The dual-ion co-regulation system enhances the ion migration rate during actuation, resulting in improved performance. Moreover, the yarn muscles can withstand high levels of isometric stress, displaying a stress of 61 times that of skeletal muscles and 8 times that of “rocking-chair” type yarn muscles at higher frequencies. This technology holds significant potential for various applications, including prosthetics and robotics.
文摘The blending of different fibers is done for the manufacturing of yarn to ensure the presence of multiple properties in the resultant yarn which is impossible if we use only one type of fiber. Tencel is regenerated cellulosic fiber & flax is natural bast fiber. Tencel shows more versatility than flax. Tencel has a softer feel with a variety of end uses. Tencel is wrinkle-prone and stiff. Tencel shows extreme strength even in wet conditions and at the same time, it is more durable than linen. The most important fact is that the heat dissipation property of flax is 5 times higher than wool & 19 times higher than silk. Linen clothing can lower the body temperature by 3 to 4 degree celsius in hot weather than clothing made of wool and silk. A yarn made of both Tencel & linen (50:50) will contain the properties of both fibers. At the same time, we can make this yarn more aesthetic by incorporating a slub. It was observed that the slub yarn made by blending Tencel and flax fiber shows better properties than the slub yarn of the same count made from the blending of cotton and flax.
基金financial support from the National Natural Science Foundation of China(52103064 and U21A2095)the Key Research and Development Program of Hubei Province(2021BAA068)National Local Joint Laboratory for Advanced Textile Processing and Clean Production(FX2022001)。
文摘Tailoring water supply to achieve confined heating has proven to be an effective strategy for boosting solar interfacial evaporation rates.However,because of salt clogging during desalination,a critical point of constriction occurs when controlling the water rate for confined heating.In this study,we demonstrate a facile and scalable weaving technique for fabricating core-sheath photothermal yarns that facilitate controlled water supply for stable and efficient interracial solar desalination.The core-sheath yarn comprises modal fibers as the core and carbon fibers as the sheaths.Because of the core-sheath design,remarkable liquid pumping can be enabled in the carbon fiber bundle of the dispersed superhydrophilic modal fibers.Our woven fabrics absorb a high proportion(92%)of the electromagnetic radiation in the solar spectrum because of the weaving structure and the carbon fiber sheath.Under one-sun(1 kW·m^(-2))illumination,our woven fabric device can achieve the highest evaporation rate(of 2.12kg·m^(-2)·h^(-1) with energy conversion efficiency:93.7%)by regulating the number of core-sheath yarns.Practical application tests demonstrate that our device can maintain high and stable desalination performance in a 5 wt%NaCl solution.
文摘In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.
基金Pre-research Foundation of Jiangnan University,China(No.206000-52210761)
文摘A new algorithm of measurement slub yarn parameter was put forward to improve precision and efficient. The basic principal of measurement slub yarn by parallel-plate capacitor was introduced,and slub yarns were tested with a measurement system developed by ourselves. Time sequence for slub length and slub space can be got. And distributions of slub length,slub space and slub scaling factor can also be obtained. The agreement can be attained compared with those original settings. Some error was analyzed also. Consequently this system is effective,and can be adopted in practice.
文摘Jamdani weaving is one of the oldest heredities of Bangladesh. From the beginning 100% cotton yarn was used to produce high quality jamdani saree. The weavers were the finest with weaving skills. Higher yarn count yarns were used to weave the jamdani saree. In course of time at present manmade fibres are also used to produce jamdani saree. The use of filament yarn may have eased the manufacturing difficulties, but the jamdani saree is missing its originality without 100% cotton. In this project, random jamdani saree sample was collected to identify the fibre composition. Samples of filament were also collected from the manufacturer and tested. It was evident that instead of cotton yarn in warp and weft silk and polyester filament yarn were used.
基金funded through Cotton Breeding Australia,a Joint Venture between CSIRO and Cotton Seed Distributors(Wee Waa,NSW 2388,Australia)。
文摘Results The population had large variations for lint yield,fibre properties,predicted yarn properties,and composite fibre quality values.Lint yield with all fibre quality traits was not correlated.When the selection was conducted first to keep those with improved fibre quality,and followed for high yields,a large proportion in the resultant populations was the same between selections based on Cottonspec predicted yarn quality and HVI-measured fibre properties.They both exceeded the selection based on FQI and Background The approach of directly testing yarn quality to define fibre quality breeding objectives and progress the selection is attractive but difficult when considering the need for time and labour.The question remains whether yarn prediction tools from textile research can serve as an alternative.In this study,using a dataset from three seasons of field testing recombinant inbred line population,Cottonspec,a software developed by the Commonwealth Scientific and Industrial Research Organisation(CSIRO)for predicting ring spun yarn quality from fibre properties measured by High Volume Instrument(HVI),was used to select improved fibre quality and lint yield in the population.The population was derived from an advanced generation inter-crossing of four CSIRO conventional commercial varieties.The Cottonspec program was able to provide an integrated index of the fibre qualities affecting yarn properties.That was compared with selection based on HVI-measured fibre properties,and two composite fibre quality variables,namely,fibre quality index(FQI),and premium and discount(PD)points.The latter represents the net points of fibre length,strength,and micronaire based on the Premiums and Discounts Schedule used in the market while modified by the inclusion of elongation.PD points.Conclusions The population contained elite segregants with improved yield and fibre properties,and Cottonspec predicted yarn quality is useful to effectively capture these elites.There is a need to further develop yarn quality prediction tools through collaborative efforts with textile mills,to draw better connectedness between fibre and yarn quality.This connection will support the entire cotton value chain research and evolution.
基金Key Research and Development Plan of Shaanxi Province,China(No.2023-YBGY-330)。
文摘In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.
文摘The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs.This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator(YARN)scheduler,called the Adaptive Node and Container Aware Scheduler(ANACRAC),that aligns cluster resources to the demands of the applications in the real world.The approach performs to leverage the user-provided configurations as a unique design to apportion nodes,or containers within the nodes,to application thresholds.Additionally,it provides the flexibility to the applications for selecting and choosing which node’s resources they want to manage and adds limits to prevent threshold breaches by adding additional jobs as needed.Node or container awareness can be utilized individually or in combination to increase efficiency.On top of this,the resource availability within the node and containers can also be investigated.This paper also focuses on the elasticity of the containers and self-adaptiveness depending on the job type.The results proved that 15%–20%performance improvement was achieved compared with the node and container awareness feature of the ANACRAC.It has been validated that this ANACRAC scheduler demonstrates a 70%–90%performance improvement compared with the default Fair scheduler.Experimental results also demonstrated the success of the enhancement and a performance improvement in the range of 60%to 200%when applications were connected with external interfaces and high workloads.
文摘针对电信大数据处理系统中存在的问题,文章提出一种基于Spark on Yarn模型的SY-TPP。在SY-TPP平台上,应用Hadoop2.0 Yarn标准,并利用Spark分布式存储技术,将SY-TPP系统的数据在内存中进行集中处理。以分级聚类算法为案例,对SY-TPP平台的开发过程进行了详细的分析。实验结果表明,TPP平台上的GB级用户可以在半个工作日内完成数据处理,而32个实体节点的SYTPP系统的速度比相同配置下的Map Reduce平台提高了10.25倍。