EM407 Sound Application Development with SQL Anywhere - PowerPoint PPT Presentation

Title: EM407 Sound Application Development with SQL Anywhere


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EM407Sound Application Development with SQL
Anywhere
Mark Culp Software Development Manager iAnywhere
Solutions mark.culp_at_ianywhere.com
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Goals of this presentation

• To help you develop applications that are
• robust,
• well designed,
• have good performance, and
• can scale with your database and number of users
• To highlight some differences between 7.0 (and
  prior) and 8.0 that can affect can affect your
  applications design

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Contents

• General considerations
• Schema design tips
• Application development tips
• Technical overview of
• Isolation levels
• Join semantics
• Cursor support in SQL Anywhere 7.0 vs. 8.0

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When should you think about performance and
scalability?

• During the design and planning stages
• Capacity planning
• Improving performance for deployed databases
• Earlier is better!

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Common areas for performance problems

• Physical database organization
• Database file characteristics
• Indexing considerations
• Schema design
• Server characteristics
• CPU, disk activity
• Network characteristics
• Application design
• Query complexity
• Trigger design
• Locking
• Workstation processing (CPU, disk)

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• Schema Design

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Schema design

• Define your tables
• Normalize your data
• Entity/Relationship (ER) modeling
• Define appropriate primary keys for all tables
• Helps in replication environments (reduces amount
  of data in log file)
• Define appropriate foreign key relationships
• Relationships needed to generate efficient join
  strategies
• Define appropriate indexes
• Don't need to create indexes for PKs or FKs
• Don't over-do it ! Only define ones that are
  useful

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Schema designprimary keys

• Data administration issues
• Ensure your application has complete control over
  key assignment and usage
• Usually a very bad idea to update a primary key
  (especially in a replication environment)
• It is exceedingly difficult to hide primary
  keys from users (or your customers)
• Key formats are very difficult to change after
  deployment

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Schema designprimary key generation

• Common problem large, composite primary keys
  that are difficult to search efficiently
• Both retrieval and update performance can suffer
• Consider surrogate primary keys change existing
  keys into unique constraints or secondary indexes
• Integer representation is the most efficient, for
  both storage and indexing
• Permits the use of autoincrement PK column hence
  the server does all the work
• Global autoincrement can generate unique PK
  values in a replicated system (now in UltraLite!)

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Schema designPK generation - autoincrement

• Autoincrement scales very well useful in many
  situations highly recommended
• Some disadvantages of autoincrement
• Often wish to differentiate keys of different
  business objects
• May desire randomized key generation for some
  applications
• Alphanumeric values can aid in data consistency
  during data entry
• Autoincrement cannot support self-checking
  identifiers
• Think about these tradeoffs when deciding on
  identifier data types

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Schema designPK generation manual

• Two other options
• Manually assign key ranges
• Cumbersome, but can work in some business
  environments
• Most prone to data entry errors
• consider self-checking or alphanumeric
  identifiers to reduce data entry problems
• Example Canadian postal codes
• e.g. N2L 3X2

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Schema designPK generation key generation
table

• Create a separate key generation table, with
  one row per business object
• To add a new key
• Initiate a new connection
• Compute the next key using the existing one as
  its basis
• Update the table, COMMIT immediately
• Several disadvantages logging, locking, possible
  contention
• Avoid design that serializes lengthy transactions

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• Application Design

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Application designcoding SQL statements

• How you write a SQL statement does matter
• Watch for join conditions involving user-defined
  functions, expressions, or type conversion
• User defined functions that have queries in them
  tie the hands of the optimizer and can be
  inefficient

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Application designcoding SQL statements

• Simplify the querys syntax if at all possible
• Select list aliases are useful to identify common
  subexpressions (including subqueries)
• e.g. Select (X10)/2 as quotient
• Eliminate unnecessary predicates, DISTINCT
  processing, etc.
• Rewrite the WHERE clause to contain as many
  conjunctive conditions as possible
• Critical for 7.0
• 8.0 now automatically rewrites where clause
• Don't replace outer joins with a subselect

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Application designprogramming considerations

• PREPARE/DESCRIBE once during initialization (or
  on first use)
• Remember to drop statements at termination -
  de-allocate statements with SQLFreeStmt()
• Bind columns whenever possible
• use SQLBindCol() instead of SQLGetData()
• Avoid COMMITing after every statement
• This is the default behavior for both JDBC and
  ODBC
• Avoid DDL in applications (including TRUNCATE
  TABLE) to avoid implicit COMMITs or CHECKPOINTs

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Application designlocking blocking

• Use cursor type appropriate to application
  function to reduce unnecessary locks
• Use SQLSetStmtOption() to set cursor attributes
• SQL_CONCURRENCY to read only
• SQL_CURSOR_TYPE to dynamic or forward-only
• Use the BLOCKING option to specify whether or not
  an application blocks on a locking conflict, or
  receives an error

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Application designopen with hold

• OPEN ... WITH HOLD only where appropriate
• All locks (except on the current row) are
  released upon COMMIT no guarantees about the
  state of the other rows
• Semantics are unclear if ROLLBACK was issued
• Consider setting the option ANSI_CLOSE_CURSORS_ON_
  ROLLBACK to force the closure of all cursors on a
  ROLLBACK statement
• Usually there is little point to using WITH HOLD
  cursors at isolation levels 2 or 3

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Application designestimating result set size

• Avoid doing so if at all possible
• Results will not be consistent in the face of
  concurrent updates
• At OPEN, SQLCA (sqlerrd2) contains an estimate
  of the result set size from the optimizer
• Use SQLRowCount() in ODBC
• If positive, estimate is accurate at the time the
  query was executed (i.e. single table scan)
• If negative, estimate is from the optimizer

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Application designestimating result set size

• Use the ROW_COUNTS option to return an accurate
  result
• For DYNAMIC cursors, query is executed twice
• Result may still change due to concurrent updates
• Consider SCROLL or INSENSITIVE cursors instead
• Result is computed only once
• INSENSITIVE result set size is fixed at OPEN
• SCROLL perform a FETCH ABSOLUTE n where n is
  large enough to force materialization of the
  entire result
• sqlerrd2 contains (n result set size)

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Application designuse of prefetch

• Prefetch is designed to reduce communication in a
  client-server environment by transferring sets of
  rows to the client in advance of a FETCH request
• Prefetch is ON by default
• To disable outright use the DisableMultiRowFetch
  connection parameter or set the Prefetch option
  to OFF
• 8.0 turns off prefetch on cursors declared
  sensitive

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Application designuse of prefetch

• Avoid the use of prefetch for updateable cursors
  at isolation level 1
• In 7.0, cursor stability is not guaranteed, as
  the client and the server are positioned on
  different rows
• In 8.0, new options to guarantee cursor stability
  
• In ESQL, use BLOCK n to limit the number of rows
  prefetched for each FETCH request
• If n is 0, prefetch is disabled

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Application designuse of prefetch

• Two new connection string parameters in 7.0.1
  PreFetchRows and PreFetchBuffer
• can specify prefetch row limit and prefetch
  buffer size, respectively, on a per-connection
  basis
• Prefetch may decrease performance if
• Application requires fewer rows than the
  prefetched amount
• Application performs FETCH ABSOLUTE or scrolls
  randomly through the rowset

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Application designbulk fetches

• For relatively large result sets, use wide
  (multi-row) fetches
• each request to the server obtains several rows
• 6.x, 7.x, and 8.0 prefetching automatically
  improves bulk fetch performance
• Application gives up cursor stability if
  prefetching is used at isolation level 1(7.0 and
  earlier)

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Application designbulk inserts

• Use LOAD TABLE where appropriate
• Use wide (multi-row) inserts
• COMMIT at regular intervals to limit size of
  rollback log
• 7.x 8.0 uses large I/Os to grow database and
  transaction log

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Application designimproving performance

• Objective is to reduce the work the engine is
  being asked to perform
• Reduce number of requests sent to the server
• Use procedures for multi-part transactions
• Consider populating and then join to a temporary
  table if needing to select multiple specific rows
• SELECT list should only contain attributes
  required by the application
• Use declared temporary tables instead of
  permanent tables to avoid logging, locking

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Application designimproving performance

• Java in the database
• Tradeoff how Java objects are fetched
• often more flexible fetch entire objects
• often more efficient fetch individual object
  values
• Minimize the need to deserialize Java columns
• use indexes to reduce the scan factor of tables
  containing Java objects
• For OLTP workloads, minimize the number of rows
  that need to be processed
• ensure that indexes can be used for ORDER BY,
  GROUP BY and DISTINCT

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Application designimproving scalability

• Be aware of the length of time your application
  will hold a lock on any specific row or table
• Request-level logging tool can assist in
  pinpointing performance problems
• PERL script to analyze log output
• Can identify the most expensive SQL queries on a
  server-wide basis
• Use TRANTEST to simulate production workload
• Use DBTRAN to review the transaction log to
  identify unnecessary updates, places to use
  temporary tables

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Application designuse of compression (new in
8.0)

• Communication compression may improve between
  client and server over a modem or WAN
• Enable using CompressYES in client connection
  string, or pc server command line switch
• Packets are compressed before encryption
• Compressed data can be less than 10 of original
  size, but depends completely on data and the
  application
• Consider increasing packet size to achieve
  greater compression and less number of packets
• Compression requires additional 46K per
  connection
• You must analyze your application's throughput

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• Some Technical Details

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Isolation levels

• Isolation levels only affect behavior of read
  requests from other connections/transactions
  writes are always locked
• Isolation levels for read requests
• 0 (default) - no locking a latch ensures that
  the entire row is consistent when retrieved from
  the disk page
• 1,2 - lock rows in the querys result, but with
  level 1 the lock is held only while the cursor is
  on that row
• 3 - lock every row read and every insertion point
  crossed during query execution
• Add/remove foreign key row requires a read lock
  on the primary row

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Isolation levels recommendations

• Use the isolation level that offers your
  application the best trade-off of consistency
  with concurrency
• NB. nothing is guaranteed at level 0 (dirty
  read)
• For isolation level 3, ensure the server can
  exploit the use of indexes to limit the amount of
  locking performed
• Specify ISOLATION LEVEL on a cursor basis instead
  of modifying the option setting

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Join semantics

• ASA supports
• INNER
• LEFT OUTER
• RIGHT OUTER
• CROSS (Cartesian product)
• FULL OUTER (new to 8.0)
• Variants
• KEY generates FK-PK equijoin condition
• NATURAL generates equijoin condition over
  columns with identical names

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Join semantics some details

• 7.x release introduces restrictions on permitted
  syntax
• Restrictions on outer references in an ON
  condition
• New option Extended_join_syntax
• By default, table expressions are left-deep
  nested
• R Join S Join T (R Join S) Join T
• Star joins are specified by using the same
  table reference (correlation name) more than once

Select From R Left Outer Join S On (R.x
S.x), R Left Outer Join T On (R.x T.x and
T.y 25)
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Join semantics some details

• Semantics of KEY joins are complex
• Verify that your query is producing the intended
  result
• See documentation for details

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Join semantics new to 8.0

• Support for FULL OUTER JOIN
• In addition to naïve nested loop join, 8.0
  introduces new join operators
• nested block, hash, sort merge
• if no ORDER BY by clause specified, order of
  results may vary depending on chosen plan so
  don't make any assumptions
• dbisql's query plan viewer can be used to
  visually display plan chosen for complex joins
• See AM33 ASA Internals

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Cursors

• ESQL cursor types
• no scroll, dynamic scroll (default), scroll,
  insensitive
• sensitive (new to 8.0)
• ODBC cursor types
• static, dynamic, keyset, mixed, forward-only
  (default)

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Cursors semantics

• Cursor semantics are dependent on
• Membership sensitivity
• Value sensitivity
• Scrollability (forward only or scrollable)
• Updatability (read-only or updateable)

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Cursors membership sensitivity

• Membership sensitivity
• Insensitive result rows are fixed at open no
  changes
• Repeatable result rows will not change once
  fetched
• Sensitive result rows will change with respect
  to concurrent inserts, deletes, and updates
• Asensitive result rows may or may not change
  depending on update activity and chosen plan

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Cursors some definitions

• Value-sensitivity (VS)
• Insensitive data values will not change once
  fetched
• Sensitive data values will change with respect
  to concurrent updates
• Asensitive data values may or may not change
  depending on update activity and chosen plan

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Cursor combinations
Row Membership Row Membership Row Membership Row Membership
Asensitive Sensitive Repeatable Insensitive
Values A ODBC unspec., ESQL dynamic n/a ESQL scroll n/a
Values S n/a ODBC dynamic, ESQL sens. n/a n/a
Values I n/a ODBC keyset n/a ODBC static, ESQL insens.

• Cursor type can be altered by server to be more
  restrictive than what was requested

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iAnywhere Solutions Highlights

• Ask the Experts - about Mobile Wireless
  Solutions
• -Mezzanine Level Room 15B
• Mon./Tues. 1130 am - 330 pm Wed. 1130 - 130
• Thurs. 9 am - 12 noon
• -Exhibit Hall - Demo Center (truck) exhibit hall
  hours
• SIG (Special Interest Group)
• - Tuesday 530pm Mobile Wireless SDCC, Upper
  level, Room 11
• Keynote - Enabling m-Business Solutions
• Wednesday 130 pm - 300 pm
• iAnywhere Solutions Developer Community
• -Excellent resource for commonly asked questions,
  newsgroups, bug
• fixes, newsletters, event listings - visit
  www.ianywhere.com/developer

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Thank you

• Questions ?
• mark.culp_at_ianywhere.com
• www.ianywhere.com