Performance Optimization of Legacy HDF5 Data for Web Object Stores
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).
This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.
This study explored three candidate architectures for serving NASA Earth Science Hierarchical Data Format Version 5 (HDF5) data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the project are: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and Network Common Data Format Version 4 (netCDF4) data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3).Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.
At the San Diego Supercomputer Center, a massive data analysis system (MDAS) is being developed to support data-intensive applications that manipulate terabyte sized data sets. The objective is to support scientific application access to data whether it is located at a Web site, stored as an object in a database, and/or storage in an archival storage system. We are developing a suite of demonstration programs which illustrate how Web, database (DBMS), and archival storage (mass storage) technologies can be integrated. An application presentation interface is being designed that integrates data access to all of these sources. We have developed a data movement interface between the Illustra object-relational database and the NSL UniTree archival storage system running in a production mode at the San Diego Supercomputer Center. With this interface, an Illustra client can transparently access data on UniTree under the control of the Illustr DBMS server. The current implementation is based on the creation of a new DBMS storage manager class, and a set of library functions that allow the manipulation and migration of data stored as Illustra 'large objects'. We have extended this interface to allow a Web client application to control data movement between its local disk, the Web server, the DBMS Illustra server, and the UniTree mass storage environment. This paper describes some of the current approaches successfully integrating these technologies. This framework is measured against a representative sample of environmental data extracted from the San Diego Ba Environmental Data Repository. Practical lessons are drawn and critical research areas are highlighted.
Cloud object stores enable data providers to reduce costs and provide uniform data servers across organizational divisions. This talk will address how new capabilities provided by cloud computing can be used with existing software so that users get the benefits provided by cloud technology (access to data at lower cost, e.g.) without disrupting their existing workflow(s). We will address ways to reduce response latency often associated with Cloud object stores and ways to simulate the hierarchy of a POSIX file system using a key-value object store. This work is based an on-going NASA EED2 project to enhance the Hyrax data server for operation in the Amazon Web Services Cloud.
The Advanced Life Support Program has recently accelerated an effort to develop an On-line Project Information System (OPIS) for research project and technology development data centralization and sharing. The core functionality of OPIS will launch in October of 2005. This paper presents the current OPIS development status. OPIS core functionality involves a Web-based annual solicitation of project and technology data directly from ALS Principal Investigators (PIS) through customized data collection forms. Data provided by PIs will be reviewed by a Technical Task Monitor (TTM) before posting the information to OPIS for ALS Community viewing via the Web. The data will be stored in an object-oriented relational database (created in MySQL(R)) located on a secure server at NASA ARC. Upon launch, OPIS can be utilized by Managers to identify research and technology development gaps and to assess task performance. Analysts can employ OPIS to obtain.
An ongoing effort is underway at NASA Amcs Research Center (ARC) tu develop an On-line Project Information System (OPIS) for the Advanced Life Support (ALS) Program. The objective of this three-year project is to develop, test, revise and deploy OPIS to enhance the quality of decision-making metrics and attainment of Program goals through improved knowledge sharing. OPIS will centrally locate detailed project information solicited from investigators on an annual basis and make it readily accessible by the ALS Community via a web-accessible interface. The data will be stored in an object-oriented relational database (created in MySQL(Trademark) located on a secure server at NASA ARC. OPE will simultaneously serve several functions, including being an R&TD status information hub that can potentially serve as the primary annual reporting mechanism. Using OPIS, ALS managers and element leads will be able to carry out informed research and technology development investment decisions, and allow analysts to perform accurate systems evaluations. Additionally, the range and specificity of information solicited will serve to educate technology developers of programmatic needs. OPIS will collect comprehensive information from all ALS projects as well as highly detailed information specific to technology development in each ALS area (Waste, Water, Air, Biomass, Food, Thermal, and Control). Because the scope of needed information can vary dramatically between areas, element-specific technology information is being compiled with the aid of multiple specialized working groups. This paper presents the current development status in terms of the architecture and functionality of OPIS. Possible implementation approaches for OPIS are also discussed.
An ongoing effort is underway at NASA Ames Research Center (ARC) to develop an On-line Project Information System (OPIS) for the Advanced Life Support (ALS) Program. The objective of this three-year project is to develop, test, revise and deploy OPIS to enhance the quality of decision-making metrics and attainment of Program goals through improved knowledge sharing. OPIS will centrally locate detailed project information solicited from investigators on an annual basis and make it readily accessible by the ALS Community via a Web-accessible interface. The data will be stored in an object-oriented relational database (created in MySQL) located on a secure server at NASA ARC. OPE will simultaneously serve several functions, including being an research and technology development (R&TD) status information hub that can potentially serve as the primary annual reporting mechanism for ALS-funded projects. Using OPIS, ALS managers and element leads will be able to carry out informed R&TD investment decisions, and allow analysts to perform accurate systems evaluations. Additionally, the range and specificity of information solicited will serve to educate technology developers of programmatic needs. OPIS will collect comprehensive information from all ALS projects as well as highly detailed information specific to technology development in each ALS area (Waste, Water, Air, Biomass, Food, Thermal, Controls and Systems Analysis). Because the scope of needed information can vary dramatically between areas, element-specific technology information is being compiled with the aid of multiple specialized working groups. This paper presents the current development status in terms of the architecture and functionality of OPIS. Possible implementation approaches for OPIS are also discussed.
An On-line Technology Information System (OTIS) is currently being developed for the Advanced Life Support (ALS) Program. This paper describes the preliminary development of OTIS, which is a system designed to provide centralized collection and organization of technology information. The lack of thorough, reliable and easily understood technology information is a major obstacle in effective assessment of technology development progress, trade studies, metric calculations, and technology selection for integrated testing. OTIS will provide a formalized, well-organized protocol to communicate thorough, accurate, current and relevant technology information between the hands-on technology developer and the ALS Community. The need for this type of information transfer system within the Solid Waste Management (SWM) element was recently identified and addressed. A SWM Technology Information Form (TIF) was developed specifically for collecting detailed technology information in the area of SWM. In the TIF, information is requested from SWM technology developers, based upon the Technology Readiness Level (TRL). Basic information is requested for low-TRL technologies, and more detailed information is requested as the TRL of the technology increases. A comparable form is also being developed for the wastewater processing element. In the future, similar forms will also be developed for the ALS elements of air revitalization, food processing, biomass production and thermal control. These ALS element-specific forms will be implemented in OTIS via a web-accessible interface,with the data stored in an object-oriented relational database (created in MySQLTM) located on a secure server at NASA Ames Research Center. With OTIS, ALS element leads and managers will be able to carry out informed research and development investment, thereby promoting technology through the TRL scale. OTIS will also allow analysts to make accurate evaluations of technology options. Additionally, the range and specificity of information solicited will help educate technology developers of programmatic needs.
Cloud based infrastructure may offer several key benefits of scalability, built in redundancy and reduced total cost of ownership as compared with a traditional data center approach. However, most of the tools and software systems developed for NASA data repositories were not developed with a cloud based infrastructure in mind and do not fully take advantage of commonly available cloud-based technologies. Object storage services are provided through all the leading public (Amazon Web Service, Microsoft Azure, Google Cloud, etc.) and private (Open Stack) clouds, and may provide a more cost-effective means of storing large data collections online. We describe a system that utilizes object storage rather than traditional file system based storage to vend earth science data. The system described is not only cost effective, but shows superior performance for running many different analytics tasks in the cloud. To enable compatibility with existing tools and applications, we outline client libraries that are API compatible with existing libraries for HDF5 and NetCDF4. Performance of the system is demonstrated using clouds services running on Amazon Web Services.
The Work Coordination Engine (WCE) is a Java application integrated into the Service Management Database (SMDB), which coordinates the dispatching and monitoring of a work order system. WCE de-queues work orders from SMDB and orchestrates the dispatching of work to a registered set of software worker applications distributed over a set of local, or remote, heterogeneous computing systems. WCE monitors the execution of work orders once dispatched, and accepts the results of the work order by storing to the SMDB persistent store. The software leverages the use of a relational database, Java Messaging System (JMS), and Web Services using Simple Object Access Protocol (SOAP) technologies to implement an efficient work-order dispatching mechanism capable of coordinating the work of multiple computer servers on various platforms working concurrently on different, or similar, types of data or algorithmic processing. Existing (legacy) applications can be wrapped with a proxy object so that no changes to the application are needed to make them available for integration into the work order system as "workers." WCE automatically reschedules work orders that fail to be executed by one server to a different server if available. From initiation to completion, the system manages the execution state of work orders and workers via a well-defined set of events, states, and actions. It allows for configurable work-order execution timeouts by work-order type. This innovation eliminates a current processing bottleneck by providing a highly scalable, distributed work-order system used to quickly generate products needed by the Deep Space Network (DSN) to support space flight operations. WCE is driven by asynchronous messages delivered via JMS indicating the availability of new work or workers. It runs completely unattended in support of the lights-out operations concept in the DSN.
Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-topeer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.
Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-to-peer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.
NASA software created to help scientists expeditiously search and organize their research documents is now aiding compliance personnel, law enforcement investigators, and the general public in their efforts to search, store, manage, and retrieve documents more efficiently. Developed at Ames Research Center, NETMARK software was designed to manipulate vast amounts of unstructured and semi-structured NASA documents. NETMARK is both a relational and object-oriented technology built on an Oracle enterprise-wide database. To ensure easy user access, Ames constructed NETMARK as a Web-enabled platform utilizing the latest in Internet technology. One of the significant benefits of the program was its ability to store and manage mission-critical data.
NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly.
NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly. Reviewed by Mark McInerney ESDIS Deputy Project Manager.
Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.