Your cart is currently empty!
Tag: Indexing
Indexing on Non-volatile Memory : Techniques, Lessons Learned and Outlook, Pa…
Indexing on Non-volatile Memory : Techniques, Lessons Learned and Outlook, Pa…
Price :200.00– 56.22
Ends on : N/A
View on eBay
Indexing on Non-volatile Memory: Techniques, Lessons Learned, and OutlookNon-volatile memory (NVM) has revolutionized the way we store and access data, providing faster, more reliable, and energy-efficient storage solutions. With the rise of NVM technologies such as NAND flash, 3D XPoint, and MRAM, there has been a growing interest in leveraging NVM for indexing purposes.
In this post, we will explore the various techniques used for indexing on NVM, the lessons learned from these implementations, and the future outlook for NVM-based indexing solutions.
Techniques for Indexing on NVM:
1. Persistent Data Structures: One of the key challenges in indexing on NVM is ensuring data consistency in the face of power failures or system crashes. Persistent data structures, such as persistent B-trees and persistent hash tables, provide a way to store data on NVM in a way that guarantees durability and consistency.
2. Copy-on-Write (CoW) Indexing: CoW indexing techniques involve creating a new version of the index whenever an update is made, while keeping the old version intact. This approach ensures that the index remains consistent even in the presence of failures, as the old version can always be recovered.
3. Log-Structured Indexing: Log-structured indexing techniques involve storing index updates in a log structure on NVM, which can be replayed in case of failures. This approach reduces the number of random writes to NVM, improving performance and durability.
Lessons Learned:
1. Write Amplification: One of the key challenges in NVM-based indexing is minimizing write amplification, which can lead to premature wear-out of NVM devices. Techniques such as batching updates and minimizing metadata writes can help reduce write amplification.
2. Garbage Collection: Garbage collection is essential for reclaiming space on NVM devices, but it can also introduce latency overheads. Efficient garbage collection algorithms that minimize the impact on indexing performance are crucial for NVM-based indexing solutions.
3. Fault Tolerance: Ensuring fault tolerance in NVM-based indexing systems is critical for maintaining data integrity. Techniques such as checksumming, logging, and replication can help mitigate the impact of failures on indexing performance.
Outlook:
The future of indexing on NVM looks promising, with ongoing research focused on improving performance, durability, and scalability of NVM-based indexing solutions. With the emergence of new NVM technologies such as SCM and NVDIMMs, we can expect to see even faster and more reliable indexing solutions in the years to come.
Overall, indexing on NVM presents exciting opportunities for improving data access and storage efficiency, and the lessons learned from current implementations will continue to inform future developments in this space. Stay tuned for more updates on indexing on NVM as this field evolves.
#Indexing #Nonvolatile #Memory #Techniques #Lessons #Learned #Outlook #Pa.., Non-volatile memory
Indexing on Non-Volatile Memory: Techniques, Lessons Learned and Outlook (SpringerBriefs in Computer Science)
Price:$44.99– $38.52
(as of Nov 23,2024 12:47:15 UTC – Details)
Publisher : Springer; 1st ed. 2024 edition (November 29, 2023)
Language : English
Paperback : 95 pages
ISBN-10 : 3031476263
ISBN-13 : 978-3031476266
Item Weight : 5.1 ounces
Dimensions : 6.14 x 0.2 x 9.21 inches
Indexing on Non-Volatile Memory: Techniques, Lessons Learned and Outlook (SpringerBriefs in Computer Science)In this post, we will explore the world of indexing on non-volatile memory (NVM), discussing various techniques, lessons learned, and the outlook for the future of this technology. Non-volatile memory, such as flash memory, is becoming increasingly popular in the world of computing due to its ability to retain data even when power is turned off.
Indexing on NVM presents a unique set of challenges and opportunities compared to traditional volatile memory systems. Techniques such as persistent data structures, log-structured indexing, and hybrid indexing have been developed to optimize performance and durability on NVM.
Throughout this post, we will discuss the lessons learned from implementing indexing on NVM, including the importance of data consistency, durability, and performance tuning. We will also explore the current state of the art in NVM indexing and provide insights into future trends and developments in this exciting field.
Whether you are a researcher, developer, or simply curious about the intersection of indexing and non-volatile memory, this post will provide valuable insights and perspectives on this cutting-edge technology. Stay tuned for more updates and discussions on indexing on non-volatile memory in the world of computer science.
#Indexing #NonVolatile #Memory #Techniques #Lessons #Learned #Outlook #SpringerBriefs #Computer #Science
Expert Performance Indexing in Azure SQL and SQL Server 2022: Toward Faster Results and Lower Maintenance Both on Premises and in the Cloud
Price:$69.99– $54.54
(as of Nov 20,2024 11:23:14 UTC – Details)
Publisher : Apress; 4th ed. edition (February 22, 2023)
Language : English
Paperback : 660 pages
ISBN-10 : 1484292146
ISBN-13 : 978-1484292143
Item Weight : 2.49 pounds
Dimensions : 7.01 x 1.49 x 10 inches
As businesses continue to rely on data-driven decision-making, the performance of their databases becomes increasingly critical. With the release of Azure SQL and SQL Server 2022, Microsoft has introduced new features and enhancements to help improve performance indexing for both on-premises and cloud environments.In this post, we will explore how the Expert Performance Indexing feature in Azure SQL and SQL Server 2022 can help organizations achieve faster results and lower maintenance costs. By leveraging advanced indexing techniques, businesses can optimize query performance, reduce storage requirements, and minimize maintenance overhead.
One of the key benefits of Expert Performance Indexing is the ability to automatically recommend and create indexes based on query patterns and usage. This proactive approach helps ensure that the database is efficiently structured to support optimal performance. Additionally, the system continuously monitors and adjusts indexes to adapt to changing workloads, further enhancing query execution speeds.
Another important aspect of Expert Performance Indexing is its support for hybrid environments. Organizations can seamlessly transition between on-premises and cloud deployments, with indexing strategies that are optimized for each environment. This flexibility allows businesses to scale their databases according to their needs, without sacrificing performance or incurring additional maintenance costs.
Overall, Expert Performance Indexing in Azure SQL and SQL Server 2022 offers a comprehensive solution for improving database performance in both on-premises and cloud environments. By leveraging advanced indexing techniques and automation capabilities, organizations can achieve faster results, lower maintenance costs, and ultimately make more informed decisions based on their data.
#Expert #Performance #Indexing #Azure #SQL #SQL #Server #Faster #Results #Maintenance #Premises #Cloud
Expert Performance Indexing in SQL Server 2019: Toward Faster Results and Lower Maintenance
Price: $41.24
(as of Nov 20,2024 00:33:58 UTC – Details)
ASIN : B0825PBF8R
Publisher : Apress; 3rd edition (November 28, 2019)
Publication date : November 28, 2019
Language : English
File size : 20600 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 801 pages
In today’s fast-paced world, businesses are constantly looking for ways to optimize their data processing and improve overall performance. One key aspect of this optimization is ensuring efficient indexing in SQL Server databases.With the release of SQL Server 2019, Microsoft has introduced several enhancements to the indexing capabilities of the database system. These improvements are designed to help users achieve faster query results and reduce the maintenance overhead associated with managing indexes.
One of the key features introduced in SQL Server 2019 is the ability to create and manage “expert” indexes. These indexes are automatically created and maintained by the database engine, based on the usage patterns and query execution plans of the database. This means that users no longer have to manually identify and create indexes for optimal performance – the database does it for them.
By leveraging expert indexes in SQL Server 2019, businesses can expect to see significant improvements in query performance, as well as reduced overhead in managing indexes. This can lead to faster results, improved user experience, and ultimately, better business outcomes.
In conclusion, the introduction of expert performance indexing in SQL Server 2019 represents a major step forward in the quest for faster results and lower maintenance in database systems. By taking advantage of these new capabilities, businesses can ensure that their data processing operations are as efficient and effective as possible.
#Expert #Performance #Indexing #SQL #Server #Faster #Results #Maintenance
