Storage structure1

Storage and File Structure
 Overview of Physical Storage Media
 Magnetic Disks
 RAID
 Tertiary Storage
 Storage Access
 File Organization
 Organization of Records in Files
 Data-Dictionary Storage

Classification of Physical Storage Media
 Data access speed
 Cost per unit of data
 Reliability
 data loss on power failure or system crash
 physical failure of the storage device
 Type of storage:
 volatile storage: loses contents when power is switched off
 non-volatile storage:
 Contents persist even when power is switched off.
 Includes secondary and tertiary storage, as well as batter-
backed up main-memory.

Physical Storage Media
 Cache – fastest and most costly form of storage; volatile; managed
by the computer system hardware.
 Main memory:
 fast access (10s to 100s of nanoseconds; 1 nanosecond = 10–9
seconds)
 generally too small (or too expensive) to store the entire
database
 capacities of up to a few Gigabytes widely used currently
 Capacities have gone up and per-byte costs have
decreased steadily and rapidly (roughly factor of 2 every 2
to 3 years)
 Volatile — contents of main memory are usually lost if a power
failure or system crash occurs.

Physical Storage Media (Cont.)
 Flash memory
 Also known as electrically erasable programmable read-only
memory (EEPROM)
 Data survives in power failure
 Data can be written at a location only once, but location can be
erased and written to again
 Can support only a limited number (10K – 1M) of write/erase
cycles.
 Erasing of memory has to be done to an entire bank of
memory
 Reads are roughly as fast as main memory
 But writes are slow (few microseconds), erase is slower
 Widely used in embedded devices such as digital cameras,
phones, and USB keys

 Magnetic-disk
 Data is stored on spinning disk, and read/written magnetically
 Primary medium for the long-term storage of data; typically stores entire
database.
 Data must be moved from disk to main memory for access, and written
back for storage
 Much slower access than main memory (more on this later)
 direct-access – possible to read data on disk in any order, unlike
magnetic tape
 Capacities range up to roughly 1.5 TB as of 2009
 Much larger capacity and cost/byte than main memory/flash memory
 Growing constantly and rapidly with technology improvements (factor
of 2 to 3 every 2 years)
 Survives power failures and system crashes
 disk failure can destroy data, but is rare

 Optical storage
 non-volatile, data is read optically from a spinning disk using
a laser
 CD-ROM (640 MB) and DVD (4.7 to 17 GB) most popular
forms
 Blu-ray disks: 27 GB to 54 GB
 Write-one, read-many (WORM) optical disks used for archival
storage (CD-R, DVD-R, DVD+R)
 Multiple write versions also available (CD-RW, DVD-RW,
DVD+RW, and DVD-RAM)
 Reads and writes are slower than with magnetic disk
 Juke-box systems, with large numbers of removable disks, a
few drives, and a mechanism for automatic loading/unloading
of disks available for storing large volumes of data

 Tape storage
 non-volatile, used primarily for backup (to recover from disk
failure), and for archival data
 sequential-access – much slower than disk
 very high capacity (40 to 300 GB tapes available)
 tape can be removed from drive  storage costs much
cheaper than disk, but drives are expensive
 Tape jukeboxes available for storing massive amounts of
data
 hundreds of terabytes (1 terabyte = 109 bytes) to even
multiple petabytes (1 petabyte = 1012 bytes)

Storage Hierarchy (Cont.)
 primary storage: Fastest media but volatile (cache, main
memory).
 secondary storage: next level in hierarchy, non-volatile,
moderately fast access time
 also called on-line storage
 E.g. flash memory, magnetic disks
 tertiary storage: lowest level in hierarchy, non-volatile, slow
access time
 also called off-line storage
 E.g. magnetic tape, optical storage

Magnetic Hard Disk Mechanism
NOTE: Diagram is schematic, and simplifies the structure of actual disk drives

Magnetic Disks
 Read-write head
 Positioned very close to the platter surface (almost touching it)
 Reads or writes magnetically encoded information.
 Surface of platter divided into circular tracks
 Over 50K-100K tracks per platter on typical hard disks
 Each track is divided into sectors.
 A sector is the smallest unit of data that can be read or written.
 Sector size typically 512 bytes
 Typical sectors per track: 500 to 1000 (on inner tracks) to 1000 to 2000 (on
outer tracks)
 To read/write a sector
 disk arm swings to position head on right track
 platter spins continually; data is read/written as sector passes under head
 Head-disk assemblies
 multiple disk platters on a single spindle (1 to 5 usually)
 one head per platter, mounted on a common arm.
 Cylinder i consists of ith track of all the platters

Magnetic Disks (Cont.)
 Earlier generation disks were susceptible to head-crashes
 Surface of earlier generation disks had metal-oxide coatings which
would disintegrate on head crash and damage all data on disk
 Current generation disks are less susceptible to such disastrous
failures, although individual sectors may get corrupted
 Disk controller – interfaces between the computer system and the disk
drive hardware.
 accepts high-level commands to read or write a sector
 initiates actions such as moving the disk arm to the right track and
actually reading or writing the data
 Computes and attaches checksums to each sector to verify that
data is read back correctly
 If data is corrupted, with very high probability stored checksum
won’t match recomputed checksum
 Ensures successful writing by reading back sector after writing it
 Performs remapping of bad sectors

Disk Subsystem
 Multiple disks connected to a computer system through a controller
 Controllers functionality (checksum, bad sector remapping) often
carried out by individual disks; reduces load on controller
 Disk interface standards families
 ATA (AT adaptor) range of standards
 SATA (Serial ATA)
 SCSI (Small Computer System Interconnect) range of standards
 SAS (Serial Attached SCSI)
 Several variants of each standard (different speeds and capabilities)

Disk Subsystem
 Disks usually connected directly to computer system
 In Storage Area Networks (SAN), a large number of disks are
connected by a high-speed network to a number of servers
 In Network Attached Storage (NAS) networked storage provides a
file system interface using networked file system protocol, instead of
providing a disk system interface

Performance Measures of Disks
 Access time – the time it takes from when a read or write request is issued to
when data transfer begins. Consists of:
 Seek time – time it takes to reposition the arm over the correct track.
 Average seek time is 1/2 the worst case seek time.
– Would be 1/3 if all tracks had the same number of sectors, and we
ignore the time to start and stop arm movement
 4 to 10 milliseconds on typical disks
 Rotational latency – time it takes for the sector to be accessed to appear
under the head.
 Average latency is 1/2 of the worst case latency.
 4 to 11 milliseconds on typical disks (5400 to 15000 r.p.m.)
 Data-transfer rate – the rate at which data can be retrieved from or stored to
the disk.
 25 to 100 MB per second max rate, lower for inner tracks
 Multiple disks may share a controller, so rate that controller can handle is
also important
 E.g. SATA: 150 MB/sec, SATA-II 3Gb (300 MB/sec)
 Ultra 320 SCSI: 320 MB/s, SAS (3 to 6 Gb/sec)
 Fiber Channel (FC2Gb or 4Gb): 256 to 512 MB/s

Performance Measures (Cont.)
 Mean time to failure (MTTF) – the average time the disk is
expected to run continuously without any failure.
 Typically 3 to 5 years
 Probability of failure of new disks is quite low, corresponding to a
“theoretical MTTF” of 500,000 to 1,200,000 hours for a new disk
 E.g., an MTTF of 1,200,000 hours for a new disk means that
given 1000 relatively new disks, on an average one will fail
every 1200 hours
 MTTF decreases as disk ages

Optimization of Disk-Block Access
 Block – a contiguous sequence of sectors from a single track
 data is transferred between disk and main memory in blocks
 sizes range from 512 bytes to several kilobytes
 Smaller blocks: more transfers from disk
 Larger blocks: more space wasted due to partially filled blocks
 Typical block sizes today range from 4 to 16 kilobytes
 Disk-arm-scheduling algorithms order pending accesses to tracks so
that disk arm movement is minimized
 elevator algorithm:
R1 R5 R2 R4R3R6
Inner track Outer track

Optimization of Disk Block Access (Cont.)
 File organization – optimize block access time by organizing the
blocks to correspond to how data will be accessed
 E.g. Store related information on the same or nearby cylinders.
 Files may get fragmented over time
 E.g. if data is inserted to/deleted from the file
 Or free blocks on disk are scattered, and newly created file
has its blocks scattered over the disk
 Sequential access to a fragmented file results in increased
disk arm movement
 Some systems have utilities to defragment the file system, in
order to speed up file access

 Nonvolatile write buffers speed up disk writes by writing blocks to a non-volatile
RAM buffer immediately
 Non-volatile RAM: battery backed up RAM or flash memory
 Even if power fails, the data is safe and will be written to disk when power
returns
 Controller then writes to disk whenever the disk has no other requests or
request has been pending for some time
 Database operations that require data to be safely stored before continuing can
continue without waiting for data to be written to disk
 Writes can be reordered to minimize disk arm movement
 Log disk – a disk devoted to writing a sequential log of block updates
 Used exactly like nonvolatile RAM
 Write to log disk is very fast since no seeks are required
 No need for special hardware (NV-RAM)
 File systems typically reorder writes to disk to improve performance
 Journaling file systems write data in safe order to NV-RAM or log disk
 Reordering without journaling: risk of corruption of file system data
Optimization of Disk Block Access (Cont.)

Flash Storage
 NOR flash vs NAND flash
 NAND flash
 used widely for storage, since it is much cheaper than NOR flash
 requires page-at-a-time read (page: 512 bytes to 4 KB)
 transfer rate around 20 MB/sec
 solid state disks: use multiple flash storage devices to provide
higher transfer rate of 100 to 200 MB/sec
 erase is very slow (1 to 2 millisecs)
 erase block contains multiple pages
 remapping of logical page addresses to physical page addresses
avoids waiting for erase
– translation table tracks mapping
» also stored in a label field of flash page
– remapping carried out by flash translation layer
 after 100,000 to 1,000,000 erases, erase block becomes
unreliable and cannot be used
– wear leveling

RAID
 RAID: Redundant Arrays of Independent Disks
 disk organization techniques that manage a large numbers of disks,
providing a view of a single disk of
 high capacity and high speed by using multiple disks in parallel,
 high reliability by storing data redundantly, so that data can be
recovered even if a disk fails
 The chance that some disk out of a set of N disks will fail is much higher than
the chance that a specific single disk will fail.
 E.g., a system with 100 disks, each with MTTF of 100,000 hours (approx.
11 years), will have a system MTTF of 1000 hours (approx. 41 days)
 Techniques for using redundancy to avoid data loss are critical with large
numbers of disks
 Originally a cost-effective alternative to large, expensive disks
 I in RAID originally stood for ``inexpensive’’
 Today RAIDs are used for their higher reliability and bandwidth.
 The “I” is interpreted as independent

Improvement of Reliability via Redundancy
 Redundancy – store extra information that can be used to rebuild
information lost in a disk failure
 E.g., Mirroring (or shadowing)
 Duplicate every disk. Logical disk consists of two physical disks.
 Every write is carried out on both disks
 Reads can take place from either disk
 If one disk in a pair fails, data still available in the other
 Data loss would occur only if a disk fails, and its mirror disk
also fails before the system is repaired
– Probability of combined event is very small
» Except for dependent failure modes such as fire or
building collapse or electrical power surges
 Mean time to data loss depends on mean time to failure,
and mean time to repair
 E.g. MTTF of 100,000 hours, mean time to repair of 10 hours
gives mean time to data loss of 500*106 hours (or 57,000 years)
for a mirrored pair of disks (ignoring dependent failure modes)

Improvement in Performance via Parallelism
 Two main goals of parallelism in a disk system:
1. Load balance multiple small accesses to increase throughput
2. Parallelize large accesses to reduce response time.
 Improve transfer rate by striping data across multiple disks.
 Bit-level striping – split the bits of each byte across multiple disks
 In an array of eight disks, write bit i of each byte to disk i.
 Each access can read data at eight times the rate of a single disk.
 But seek/access time worse than for a single disk
 Bit level striping is not used much any more
 Block-level striping – with n disks, block i of a file goes to disk (i
mod n) + 1
 Requests for different blocks can run in parallel if the blocks
reside on different disks
 A request for a long sequence of blocks can utilize all disks in
parallel

RAID Levels
 Schemes to provide redundancy at lower cost by using disk
striping combined with parity bits
 Different RAID organizations, or RAID levels, have differing
cost, performance and reliability characteristics
 RAID Level 1: Mirrored disks with block striping
 Offers best write performance.
 Popular for applications such as storing log files in a database system.
 RAID Level 0: Block striping; non-redundant.
 Used in high-performance applications where data loss is not critical.

RAID Levels (Cont.)
 RAID Level 2: Memory-Style Error-Correcting-Codes (ECC) with bit
striping.
 RAID Level 3: Bit-Interleaved Parity
 a single parity bit is enough for error correction, not just
detection, since we know which disk has failed
 When writing data, corresponding parity bits must also be
computed and written to a parity bit disk
 To recover data in a damaged disk, compute XOR of bits
from other disks (including parity bit disk)

RAID Levels (Cont.)
 RAID Level 3 (Cont.)
 Faster data transfer than with a single disk, but fewer I/Os per
second since every disk has to participate in every I/O.
 Subsumes Level 2 (provides all its benefits, at lower cost).
 RAID Level 4: Block-Interleaved Parity; uses block-level striping,
and keeps a parity block on a separate disk for corresponding
blocks from N other disks.
 When writing data block, corresponding block of parity bits must
also be computed and written to parity disk
 To find value of a damaged block, compute XOR of bits from
corresponding blocks (including parity block) from other disks.

RAID Levels (Cont.)
 Provides higher I/O rates for independent block reads than Level 3
 block read goes to a single disk, so blocks stored on different
disks can be read in parallel
 Provides high transfer rates for reads of multiple blocks than no-
striping
 Before writing a block, parity data must be computed
 Can be done by using old parity block, old value of current block
and new value of current block (2 block reads + 2 block writes)
 Or by recomputing the parity value using the new values of
blocks corresponding to the parity block
– More efficient for writing large amounts of data sequentially
 Parity block becomes a bottleneck for independent block writes
since every block write also writes to parity disk

RAID Levels (Cont.)
 RAID Level 5: Block-Interleaved Distributed Parity; partitions data and
parity among all N + 1 disks, rather than storing data in N disks and
parity in 1 disk.
 E.g., with 5 disks, parity block for nth set of blocks is stored on disk
(n mod 5) + 1, with the data blocks stored on the other 4 disks.

RAID Levels (Cont.)
 Higher I/O rates than Level 4.
 Block writes occur in parallel if the blocks and their parity
blocks are on different disks.
 Subsumes Level 4: provides same benefits, but avoids bottleneck
of parity disk.
 RAID Level 6: P+Q Redundancy scheme; similar to Level 5, but
stores extra redundant information to guard against multiple disk
failures.
 Better reliability than Level 5 at a higher cost; not used as widely.

Choice of RAID Level
 Factors in choosing RAID level
 Monetary cost
 Performance: Number of I/O operations per second, and
bandwidth during normal operation
 Performance during failure
 Performance during rebuild of failed disk
 Including time taken to rebuild failed disk
 RAID 0 is used only when data safety is not important
 E.g. data can be recovered quickly from other sources
 Level 2 and 4 never used since they are subsumed by 3 and 5
 Level 3 is not used anymore since bit-striping forces single block
reads to access all disks, wasting disk arm movement, which
block striping (level 5) avoids
 Level 6 is rarely used since levels 1 and 5 offer adequate safety
for most applications

Choice of RAID Level (Cont.)
 Level 1 provides much better write performance than level 5
 Level 5 requires at least 2 block reads and 2 block writes to write
a single block, whereas Level 1 only requires 2 block writes
 Level 1 preferred for high update environments such as log disks
 Level 1 had higher storage cost than level 5
 disk drive capacities increasing rapidly (50%/year) whereas disk
access times have decreased much less (x 3 in 10 years)
 I/O requirements have increased greatly, e.g. for Web servers
 When enough disks have been bought to satisfy required rate of
I/O, they often have spare storage capacity
 so there is often no extra monetary cost for Level 1!
 Level 5 is preferred for applications with low update rate,
and large amounts of data
 Level 1 is preferred for all other applications

Hardware Issues
 Software RAID: RAID implementations done entirely in software,
with no special hardware support
 Hardware RAID: RAID implementations with special hardware
 Use non-volatile RAM to record writes that are being executed
 Beware: power failure during write can result in corrupted disk
 E.g. failure after writing one block but before writing the
second in a mirrored system
 Such corrupted data must be detected when power is
restored
– Recovery from corruption is similar to recovery from
failed disk
– NV-RAM helps to efficiently detected potentially
corrupted blocks
» Otherwise all blocks of disk must be read and
compared with mirror/parity block

Hardware Issues (Cont.)
 Latent failures: data successfully written earlier gets damaged
 can result in data loss even if only one disk fails
 Data scrubbing:
 continually scan for latent failures, and recover from copy/parity
 Hot swapping: replacement of disk while system is running, without power
down
 Supported by some hardware RAID systems,
 reduces time to recovery, and improves availability greatly
 Many systems maintain spare disks which are kept online, and used as
replacements for failed disks immediately on detection of failure
 Reduces time to recovery greatly
 Many hardware RAID systems ensure that a single point of failure will not
stop the functioning of the system by using
 Redundant power supplies with battery backup
 Multiple controllers and multiple interconnections to guard against
controller/interconnection failures

Optical Disks
 Compact disk-read only memory (CD-ROM)
 Removable disks, 640 MB per disk
 Seek time about 100 msec (optical read head is heavier and slower)
 Higher latency (3000 RPM) and lower data-transfer rates (3-6 MB/s)
compared to magnetic disks
 Digital Video Disk (DVD)
 DVD-5 holds 4.7 GB , and DVD-9 holds 8.5 GB
 DVD-10 and DVD-18 are double sided formats with capacities of 9.4
GB and 17 GB
 Blu-ray DVD: 27 GB (54 GB for double sided disk)
 Slow seek time, for same reasons as CD-ROM
 Record once versions (CD-R and DVD-R) are popular
 data can only be written once, and cannot be erased.
 high capacity and long lifetime; used for archival storage
 Multi-write versions (CD-RW, DVD-RW, DVD+RW and DVD-RAM)
also available

Magnetic Tapes
 Hold large volumes of data and provide high transfer rates
 Few GB for DAT (Digital Audio Tape) format, 10-40 GB with DLT
(Digital Linear Tape) format, 100 GB+ with Ultrium format, and
330 GB with Ampex helical scan format
 Transfer rates from few to 10s of MB/s
 Tapes are cheap, but cost of drives is very high
 Very slow access time in comparison to magnetic and optical disks
 limited to sequential access.
 Some formats (Accelis) provide faster seek (10s of seconds) at
cost of lower capacity
 Used mainly for backup, for storage of infrequently used information,
and as an off-line medium for transferring information from one
system to another.
 Tape jukeboxes used for very large capacity storage
 Multiple petabyes (1015 bytes)

File Organization, Record Organization
and Storage Access

File Organization
 The database is stored as a collection of files. Each file is a
sequence of records. A record is a sequence of fields.
 One approach:
assume record size is fixed
each file has records of one particular type only
different files are used for different relations
This case is easiest to implement; will consider variable length
records later.

Fixed-Length Records
 Simple approach:
 Store record i starting from byte n  (i – 1), where n is the size of
each record.
 Record access is simple but records may cross blocks
 Modification: do not allow records to cross block boundaries
 Deletion of record i:
alternatives:
 move records i + 1, . . ., n
to i, . . . , n – 1
 move record n to i
 do not move records, but
link all free records on a
free list

Deleting record 3 and compacting

Deleting record 3 and moving last record

Free Lists
 Store the address of the first deleted record in the file header.
 Use this first record to store the address of the second deleted record,
and so on
 Can think of these stored addresses as pointers since they “point” to
the location of a record.
 More space efficient representation: reuse space for normal attributes
of free records to store pointers. (No pointers stored in in-use records.)

Variable-Length Records
 Variable-length records arise in database systems in several ways:
 Storage of multiple record types in a file.
 Record types that allow variable lengths for one or more fields such as
strings (varchar)
 Record types that allow repeating fields (used in some older data
models).
 Attributes are stored in order
 Variable length attributes represented by fixed size (offset, length), with
actual data stored after all fixed length attributes
 Null values represented by null-value bitmap

Variable-Length Records: Slotted Page Structure
 Slotted page header contains:
 number of record entries
 end of free space in the block
 location and size of each record
 Records can be moved around within a page to keep them contiguous
with no empty space between them; entry in the header must be
updated.
 Pointers should not point directly to record — instead they should
point to the entry for the record in header.

Organization of Records in Files
 Heap – a record can be placed anywhere in the file where there
is space
 Sequential – store records in sequential order, based on the
value of the search key of each record
 Hashing – a hash function computed on some attribute of each
record; the result specifies in which block of the file the record
should be placed
 Records of each relation may be stored in a separate file. In a
multitable clustering file organization records of several
different relations can be stored in the same file
 Motivation: store related records on the same block to
minimize I/O

Sequential File Organization
 Suitable for applications that require sequential processing of
the entire file
 The records in the file are ordered by a search-key

Sequential File Organization (Cont.)
 Deletion – use pointer chains
 Insertion –locate the position where the record is to be inserted
 if there is free space insert there
 if no free space, insert the record in an overflow block
 In either case, pointer chain must be updated
 Need to reorganize the file
from time to time to restore
sequential order

Multitable Clustering File Organization
Store several relations in one file using a multitable clustering
file organization
department
instructor
multitable clustering
of department and
instructor

Multitable Clustering File Organization (cont.)
 good for queries involving department instructor, and for queries
involving one single department and its instructors
 bad for queries involving only department
 results in variable size records
 Can add pointer chains to link records of a particular relation

Data Dictionary Storage
 Information about relations
 names of relations
 names, types and lengths of attributes of each relation
 names and definitions of views
 integrity constraints
 User and accounting information, including passwords
 Statistical and descriptive data
 number of tuples in each relation
 Physical file organization information
 How relation is stored (sequential/hash/…)
 Physical location of relation
 Information about indices (Chapter 11)
The Data dictionary (also called system catalog) stores
metadata; that is, data about data, such as

Relational Representation of System Metadata
 Relational
representation on
disk
 Specialized data
structures
designed for
efficient access, in
memory

Storage Access
 A database file is partitioned into fixed-length storage units called
blocks. Blocks are units of both storage allocation and data
transfer.
 Database system seeks to minimize the number of block transfers
between the disk and memory. We can reduce the number of
disk accesses by keeping as many blocks as possible in main
memory.
 Buffer – portion of main memory available to store copies of disk
blocks.
 Buffer manager – subsystem responsible for allocating buffer
space in main memory.

Buffer Manager
 Programs call on the buffer manager when they need a block
from disk.
1. If the block is already in the buffer, buffer manager returns
the address of the block in main memory
2. If the block is not in the buffer, the buffer manager
1. Allocates space in the buffer for the block
1. Replacing (throwing out) some other block, if required,
to make space for the new block.
2. Replaced block written back to disk only if it was
modified since the most recent time that it was written
to/fetched from the disk.
2. Reads the block from the disk to the buffer, and returns
the address of the block in main memory to requester.

Buffer-Replacement Policies
 Most operating systems replace the block least recently used
(LRU strategy)
 Idea behind LRU – use past pattern of block references as a
predictor of future references
 Queries have well-defined access patterns (such as sequential
scans), and a database system can use the information in a user’s
query to predict future references
 LRU can be a bad strategy for certain access patterns involving
repeated scans of data
 For example: when computing the join of 2 relations r and s
by a nested loops
for each tuple tr of r do
for each tuple ts of s do
if the tuples tr and ts match …
 Mixed strategy with hints on replacement strategy provided
by the query optimizer is preferable

Buffer-Replacement Policies (Cont.)
 Pinned block – memory block that is not allowed to be written
back to disk.
 Toss-immediate strategy – frees the space occupied by a block
as soon as the final tuple of that block has been processed
 Most recently used (MRU) strategy – system must pin the
block currently being processed. After the final tuple of that block
has been processed, the block is unpinned, and it becomes the
most recently used block.
 Buffer manager can use statistical information regarding the
probability that a request will reference a particular relation
 E.g., the data dictionary is frequently accessed. Heuristic:
keep data-dictionary blocks in main memory buffer
 Buffer managers also support forced output of blocks for the
purpose of recovery (more in Chapter 16)

Storage structure1

More Related Content

What's hot (18)

Similar to Storage structure1 (20)

Recently uploaded (20)

Storage structure1