Flash Solid State Disk Write Endurance in Database Environments

The purpose of this document is to provide the reader valuable insights into the write endurance aspects of using Flash memory-based solid state disks within typically encountered database applications in an enterprise environment. The same principles used in this paper will also apply to applications that are flat file based as opposed to relational databases.

Despite having already considered using non-volatile solid state disks to complement traditional mechanical drive based storage in an attempt to enhance overall application performance, the reader may want to be advised of how any issues concerning solid state flash disk write endurance limitations are addressed with confidence.

Flash Memory and Write Endurance

Flash memory is a form of EEPROM that allows multiple memory locations to be erased or written in one programming operation. Normal EEPROM only allows one location at a time to be erased or written, meaning that Flash can operate at higher effective speeds when the systems using it read and write to different locations at the same time. All types of Flash memory and EEPROM wear out after a certain number of erase operations.

Flash memory is classified into two main types: NOR Flash and NAND Flash. The names refer to the type of logic gate used in each storage cell. Some flash solid state disks utilize NAND Flash since it has faster erase and write times, higher density, and lower cost per bit than NOR Flash, and about ten times the endurance. Most NAND Flash manufacturers today claim a write endurance of 1 million write cycles per block.

Intelligent Flash drives will use a combination of write-back cache, wear leveling and bad block auto-remapping techniques that virtually extend Flash memory erase/write endurance by several orders of magnitude.

Database Application I/O Workload Profile

Let us examine different database applications and database functions, and their typical I/O workload profiles that determine the nature of access to disk. They will usually differ in terms of the frequency and size of the I/O requests, and whether or not access to the data will mostly be sequential or random.

The key high-level application types include transaction processing, decision support and batch processing systems. In this section we will examine the various access patterns on database files and select a typical application for the purpose of studying solid state flash disk write endurance when used within a database environment.

A study of the best practices in using SSD to derive performance benefits where hot (heavily used) files are used in a database application scenario is another extensive topic that is better discussed in a separate paper. Batch Processing

In enterprise applications, batch processing is the most likely application to produce significant sequential I/O on the data files. Typical examples will be bulk loading of data warehouses, high-speed data acquisition and video-on-demand content loading applications. Disk access profile will mostly be sequential in nature and with a very high percentage of writes versus reads, which essentially poses a worst case scenario for determining Flash memory disk write endurance.

Decision Support System (DSS)

Decision support or data warehousing applications perform queries on a large amount of data, usually gathered from OLTP applications, and provide competitive information to the decision-makers in an organization. Decision support systems must handle complex queries on data that is less frequently updated than OLTP systems.

DSS is characteristic of multiple users executing complicated joins and aggregations on large sets of data. Even though many of the operations could use some sequential processing, contention with other users and join and indexing operations result in a fairly random access pattern to the data and index files.

Assuming that the database is dedicated to the DSS application, few updates will be done to the database during heavy query. Due to its mostly query-based nature versus updates for disk access, DSS applications may not be the best candidate for a study on the write endurance of flash solid state disks.

Online Transaction Processing (OLTP)

Online transaction processing (OLTP) applications are high-throughput, insert/update intensive systems. These systems are usually characterized by constantly growing large volumes of data that large number of users access concurrently. Examples of typical OLTP applications are order processing applications, banking applications and reservation systems.

The I/O profile resulting from this load is heavy random reads and writes across the data and index files. The transaction logs, however, are hit with a heavy stream of sequential write operations of 2K-16K bytes in size. This makes an OLTP application a better example of a typical database application for our purpose when compared to DSS and batch applications.

The choice of the type of RAID for the solid state flash disk's use of the database or parts of it will impact more on the system's overall performance improvements and not on write endurance of the flash solid state disk. The case presented in the succeeding sections uses interleaved parity RAID 5 that involves one physical write to the stripe (or drive) per logical write, just like other basic types of RAID (0, 1, 2, 3 or 4).

Characteristics of OLTP and DSS are summarized in Table 1.

	OLTP	DSS
Transaction	Regular business transactions Heavy on retrievals and updates Short and quick queries	Ad hoc queries on historical data Heavy on retrievals, light on updates Complex and long running queries
Performance	User response time critical	Complex queries User response not critical
Concurrent Users	Many	Few
Disk I/O	60 - 80 % reads 20 - 40% writes Frequent disk writes New records are continually added and existing records are updated or deleted	90 % reads, 10 % writes (except during builds) Relatively few disk writes Pages are moved in and out of cache

Table 1: Characteristics of OLTP and DSS

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