This chapter contains information comparing the Microsoft SQL Server or Sybase Adaptive Server database and the Oracle database. It contains the following sections:
The schema contains the definitions of the tables, views, indexes, users, constraints, stored procedures, triggers, and other database-specific objects. Most relational databases work with similar objects.
The schema migration topics discussed here include the following:
There are many similarities between schema objects in Oracle and schema objects in Microsoft SQL Server or Sybase Adaptive Server. However, some schema objects differ between these databases, as shown in the following table:
Table 2-1 Schema Objects in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Oracle | Microsoft SQL Server or Sybase Adaptive Server |
|---|---|
|
Database |
Database |
|
Schema |
Database and database owner (DBO) |
|
Tablespace |
Database |
|
User |
User |
|
Role |
Group/Role |
|
Table |
Table |
|
Temporary tables |
Temporary tables |
|
Cluster |
N/A |
|
Column-level check constraint |
Column-level check constraint |
|
Column default |
Column default |
|
Unique key |
Unique key or identity property for a column |
|
Primary key |
Primary key |
|
Foreign key |
Foreign key |
|
Index |
Non-unique index |
|
PL/SQL Procedure |
Transact-SQL (T-SQL) stored procedure |
|
PL/SQL Function |
T-SQL stored function |
|
Packages |
N/A |
|
AFTER triggers |
Triggers |
|
BEFORE triggers |
Complex rules |
|
Triggers for each row |
N/A |
|
Synonyms |
N/A |
|
Sequences |
Identity property for a column |
|
Snapshot |
N/A |
|
View |
View |
Reserved words differ between Oracle and Microsoft SQL Server or Sybase Adaptive Server. Many Oracle reserved words are valid object or column names in Microsoft SQL Server or Sybase Adaptive Server. For example, DATE is a reserved word in Oracle, but it is not a reserved word in Microsoft SQL Server or Sybase Adaptive Server. Therefore, no column is allowed to have the name DATE in Oracle, but a column can be named DATE in Microsoft SQL Server or Sybase Adaptive Server. Use of reserved words as schema object names makes it impossible to use the same names across databases.
You should choose a schema object name that is unique by case and by at least one other characteristic, and ensure that the object name is not a reserved word from either database.
For a list of reserved words in Oracle, see Oracle Database SQL Language Reference.
This section discusses the many table design issues that you need to consider when converting Microsoft SQL Server or Sybase Adaptive Server databases to Oracle. These issues are discussed under the following headings:
This section describes conversion considerations for the following data types:
The date/time precision in Microsoft SQL Server or Sybase Adaptive Server is 1/300th of a second. Oracle has the data type TIMESTAMP which has a precision of 1/100000000th of a second. Oracle also has a DATE data type that stores date and time values accurate to one second. SQL Developer has a default mapping to the DATE data type.
For applications that require finer date/time precision than seconds, the TIMESTAMP data type should be selected for the data type mapping of date data types in Microsoft SQL Server or Sybase Adaptive Server. The databases store point-in-time values for DATE and TIME data types.
As an alternative, if a Microsoft SQL Server or Sybase Adaptive Server application uses the DATETIME column to provide unique IDs instead of point-in-time values, replace the DATETIME column with a SEQUENCE in the Oracle schema definition.
In the following examples, the original design does not allow the DATETIME precision to exceed seconds in the Oracle table. This example assumes that the DATETIME column is used to provide unique IDs. If millisecond precision is not required, the table design outlined in the following example is sufficient:
Original Table Design
Microsoft SQL Server or Sybase Adaptive Server:
CREATE TABLE example_table (datetime_column datetime not null, text_column text null, varchar_column varchar(10) null)
Oracle:
CREATE TABLE example_table (datetime_column date not null, text_column long null, varchar_column varchar2(10) null)
The following design allows the value of the sequence to be inserted into the integer_column. This allows you to order the rows in the table beyond the allowed precision of one second for DATE data type fields in Oracle. If you include this column in the Microsoft SQL Server or Sybase Adaptive Server table, you can keep the same table design for the Oracle database.
Revised Table Design
Microsoft SQL Server or Sybase Adaptive Server:
CREATE TABLE example_table (datetime_column datetime not null, integer_column int null, text_column text null, varchar_column varchar(10) null)
Oracle:
CREATE TABLE example_table (datetime_column date not null, integer_column number null, text_column long null, varchar_column varchar2(10) null)
For the Microsoft SQL Server or Sybase Adaptive Server database, the value in the integer_column is always NULL. For Oracle, the value for the field integer_column is updated with the next value of the sequence.
Create the sequence by issuing the following command:
CREATE SEQUENCE datetime_seq
Values generated for this sequence start at 1 and are incremented by 1.
Many applications do not use DATETIME values as UNIQUE IDs, but still require the date/time precision to be higher than secondS. For example, the timestamp of a scientific application may have to be expressed in milliseconds, microseconds, and nanoseconds. The precision of the Microsoft SQL Server or Sybase Adaptive Server DATETIME data type is 1/300th of a second; the precision of the Oracle DATE data type is one second. The Oracle TIMESTAMP data type has a precision to 1/100000000th of a second. However, the precision recorded is dependent on the operating system.
The physical and logical storage methods for IMAGE and TEXT data differ from Oracle to Microsoft SQL Server or Sybase Adaptive Server. In Microsoft SQL Server or Sybase Adaptive Server, a pointer to the IMAGE or TEXT data is stored with the rows in the table while the IMAGE or TEXT data is stored separately. This arrangement allows multiple columns of IMAGE or TEXT data per table. In Oracle, IMAGE data may be stored in a BLOB type field and TEXT data may be stored in a CLOB type field. Oracle allows multiple BLOB and CLOB columns per table. BLOBS and CLOBS may or may not be stored in the row depending on their size.
If the Microsoft SQL Server or Sybase Adaptive Server TEXT column is such that the data never exceeds 4000 bytes, convert the column to an Oracle VARCHAR2 data type column instead of a CLOB column. An Oracle table can define multiple VARCHAR2 columns. This size of TEXT data is suitable for most applications.
This Microsoft SQL Server or Sybase Adaptive Server T-SQL-specific enhancement to SQL allows users to define and name their own data types to supplement the system data types. A user-defined data type can be used as the data type for any column in the database. Defaults and rules (check constraints) can be bound to these user-defined data types, which are applied automatically to the individual columns of these user-defined data types.
When migrating to Oracle PL/SQL, SQL Developer determines the base data type for each user-defined data type, and it finds the equivalent PL/SQL data type.
Note:
User-defined data types make the data definition language code and procedural SQL code less portable across different database servers.You can define a primary key for a table in Microsoft SQL Server or Sybase Adaptive Server. Primary keys can be defined in a CREATE TABLE statement or an ALTER TABLE statement.
Oracle provides declarative referential integrity. A primary key can be defined as part of a CREATE TABLE or an ALTER TABLE statement. Oracle internally creates a unique index to enforce the integrity.
You can define a foreign key for a table in Microsoft SQL Server or Sybase Adaptive Server. Foreign keys can be defined in a CREATE TABLE statement or an ALTER TABLE statement.
Oracle provides declarative referential integrity. A CREATE TABLE or ALTER TABLE statement can add foreign keys to the table definition. For information about referential integrity constraints, see Oracle Database Concepts.
You can define a unique key for a table in Microsoft SQL Server or Sybase Adaptive Server. Unique keys can be defined in a CREATE TABLE statement or an ALTER TABLE statement.
Oracle defines unique keys as part of CREATE TABLE or ALTER TABLE statements. Oracle internally creates unique indexes to enforce these constraints.
Unique keys map one-to-one from Microsoft SQL Server or Sybase Adaptive Server to Oracle.
Check constraints can be defined in a CREATE TABLE statement or an ALTER TABLE statement in Microsoft SQL Server or Sybase Adaptive Server. Multiple check constraints can be defined on a table. A table-level check constraint can reference any column in the constrained table. A column can have only one check constraint. A column-level check constraint can reference only the constrained column. These check constraints support complex regular expressions.
Oracle defines check constraints as part of the CREATE TABLE or ALTER TABLE statements. A check constraint is defined at the TABLE level and not at the COLUMN level. Therefore, it can reference any column in the table. Oracle, however, does not support complex regular expressions.
create rule phone_rule as @phone_number like "([0-9][0-9][0-9])[0-9][0-9][0-9]-[0-9][0-9][0-9][0-9]"
This rule passes all the phone numbers that resemble the following: (650)506-7000
This rule fails all the phone numbers that resemble the following:
650-506-7000 650-GET-HELP
There are a few ways to implement this INTEGRITY constraint in Oracle:
Simulate the behavior of phone-rule in a check constraint using a combination of SUBSTR, TRANSLATE, and LIKE clauses
Write a trigger and use PL/SQL
Table-level check constraints from Microsoft SQL Server or Sybase Adaptive Server databases map one-to-one with Oracle check constraints. You can implement the column-level check constraints from the Microsoft SQL Server or Sybase Adaptive Server database to Oracle table-level check constraints. While converting the regular expressions, convert all simple regular expressions to check constraints in Oracle. Microsoft SQL Server or Sybase Adaptive Server check constraints with complex regular expressions can be either reworked as check constraints including a combination of simple regular expressions, or you can write Oracle database triggers to achieve the same functionality.
This chapter provides detailed descriptions of the differences in data types used by Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. Specifically, this chapter contains the following information:
A table showing the base Microsoft SQL Server or Sybase Adaptive Server data types available and how they are mapped to Oracle data types
Recommendations based on the information listed in the table
Table 2-2 Data Types in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Description | Oracle | Comments |
|---|---|---|---|
|
INTEGER |
Four-byte integer, 31 bits, and a sign. May be abbreviated as "INT" (this abbreviation was required prior to version 5). |
NUMBER(10) |
It is possible to place a table constraint on columns of this type (as an option) to force values between -2^31 and2^31. Or, place appropriate constraints such as: STATE_NO between 1 and 50 |
|
SMALLINT |
Two-byte integer, 15 bits, and a sign. |
NUMBER(5) |
It is possible to place a table constraint on columns of this type (optionally) to force values between -2^15 and 2^15. Or, place appropriate constraints such as: STATE_NO between 1 and 50 |
|
TINYINT |
One byte integer, 8 bits and no sign. Holds whole numbers between 0 and 255. |
NUMBER(3) |
You may add a check constraint of (x between 0 and 255) where x is column name. |
|
REAL |
Floating point number. Storage is four bytes and has a binary precision of 24 bits, a 7-digit precision. Data can range from –3.40E+38 to 3.40E+38. |
FLOAT |
The ANSI data type conversion to Oracle for REAL is FLOAT(63). By default, SQL Developer maps REAL to FLOAT(24) that stores up to 8 significant decimal digits in Oracle. The Oracle NUMBER data type is used to store both fixed and floating-point numbers in a format that is compatible with decimal arithmetic. You may want to add a check constraint to constrain range of values. Also, you get different answers when performing operations on this data type as the Oracle NUMBER type is more precise and portable than REAL. Floating-point numbers can be specified in Oracle in the following format: FLOAT[(b)]. Where [(b)] is the binary precision b and can range from 1 to 126. [(b)] defaults to 126. To check what a particular binary precision is in terms of decimal precision, multiply [(b)] by 0.30103 and round up to the next whole number. |
|
A floating point number. This column has 15-digit precision. |
FLOAT |
The ANSI data type conversion to Oracle for FLOAT(p) is FLOAT(p). The ANSI data type conversion to Oracle for DOUBLE PRECISION is FLOAT(126). By default, SQL Developer maps FLOAT to FLOAT(53), that stores up to 16 significant decimal digits in Oracle. The Oracle NUMBER data type is used to store both fixed and floating-point numbers in a format compatible with decimal arithmetic.You get different answers when performing operations on this type due to the fact that the Oracle NUMBER type is much more precise and portable than FLOAT, but it does not have the same range. The NUMBER data type data can range from -9.99.99E+125 to 9.99.99E+125 (38 nines followed by 88 zeros). NOTE: If you try to migrate floating point data greater than or equal to 1.0E+126 then SQL Developer will fail to insert this data in the Oracle database and1 will return an error.This also applies to negative values less than or equal to -1.0E+126. |
|
|
Floating-point numbers can be specified in Oracle using FLOAT[(b)], where [(b)] is the binary precision [(b)] and can range from 1 to 126. [(b)] defaults to 126.To check what a particular binary precision is in terms of decimal precision multiply [(b)] by 0.30103 and round up to the next whole number. If they are outside of the range, large floating-point numbers will overflow, and small floating-point numbers will underflow. |
|||
|
BIT |
A Boolean 0 or 1 stored as one bit of a byte. Up to 8-bit columns from a table may be stored in a single byte, even if not contiguous. Bit data cannot be NULL, except for Microsoft SQL Server 7.0, where null is allowed by the BIT data type. |
NUMBER(1) |
In Oracle, a bit is stored in a number(1) (or char). In Oracle, it is possible to store bits in a char or varchar field (packed) and supply PL/SQL functions to set / unset / retrieve / query on them. |
|
Fixed-length string of exactly n 8-bit characters, blank padded. Synonym for CHARACTER. 0 < n < 256 for Microsoft SQL Server or Sybase Adaptive Server. 0 < n < 8000 for Microsoft SQL Server 7.0. |
CHAR(n) |
Pro*C client programs must use mode=ansi to have characters interpreted correctly for string comparison, mode=oracle otherwise. A CHAR data type with a range of 2001 to 4000 is invalid. SQL Developer automatically converts a CHAR datatype with this range to VARCHAR2. |
|
|
Varying-length character string. 0 < n < 256 for Microsoft SQL Server or Sybase Adaptive Server. 0 < n < 8000 for Microsoft SQL Server 7.0. |
VARCHAR2(n) |
||
|
TEXT |
Character string of 8-bit bytes allocated in increments of 2k pages. "TEXT" is stored as a linked-list of 2024-byte pages, blank padded. TEXT columns can hold up to (231-1) characters. |
CLOB |
The CLOB field can hold up to 4GB. |
|
IMAGE |
Binary string of 8-bit bytes. Holds up to (231-1) bytes of binary data. |
BLOB |
The BLOB field can hold up to 4GB. |
|
BINARY(n) |
Fixed length binary string of exactly n 8-bit bytes. 0 < n < 256 for Microsoft SQL Server or Sybase Adaptive Server. 0 < n < 8000 for Microsoft SQL Server 7.0. |
RAW(n)/BLOB |
|
|
VARBINARY(n) |
Varying length binary string of up to n 8-bit bytes. 0 < n < 256 for Microsoft SQL Server or Sybase Adaptive Server. 0 < n < 8000 for Microsoft SQL Server 7.0. |
RAW(n)/BLOB |
|
|
Date and time are stored as two 4-byte integers. The date portion is represented as a count of the number of days offset from a baseline date (1/1/1900) and is stored in the first integer. Permitted values are legal dates between 1st January, 1753 AD and 31st December, 9999 AD. Permitted values in the time portion are legal times in the range 0 to 25920000. Accuracy is to the nearest 3.33 milliseconds with rounding downward. Columns of type DATETIME have a default value of 1/1/1900. |
DATE |
The precision of DATE in Oracle and DATETIME in Microsoft SQL Server or Sybase Adaptive Server is different. The DATETIME data type has higher precision than the DATE data type. This may have some implications if the DATETIME column is supposed to be UNIQUE. In Microsoft SQL Server or Sybase Adaptive Server, the column of type DATETIME can contain UNIQUE values because the DATETIME precision in Microsoft SQL Server or Sybase Adaptive Server is to the hundredth of a second. In Oracle, however, these values may not be UNIQUE as the date precision is to the second. You can replace a DATETIME column with two columns, one with data type DATE and another with a sequence, in order to get the UNIQUE combination. It is preferable to store hundredths of seconds in the second column. The Oracle TIMESTAMP data type can also be used. It has a precision of 1/10000000th of a second. |
|
|
SMALL-DATETIME |
Date and time stored as two 2-byte integers. Date ranges from 1/1/1900 to 6/6/2079. Time is the count of the number of minutes since midnight. |
DATE |
With optional check constraint to validate the smaller range. |
|
MONEY |
A monetary value represented as an integer portion and a decimal fraction, and stored as two 4-byte integers. Accuracy is to the nearest 1/10,000. When inputting Data of this type it should be preceded by a dollar sign ($). In the absence of the "$" sign, Microsoft SQL Server or Sybase Adaptive Server creates the value as a float. Monetary data values can range from -922,337,203,685,477.5808 to 922,337,203,685,477.5807, with accuracy to a ten-thousandth of a monetary unit. Storage size is 8 bytes. |
NUMBER(19,4) |
Microsoft SQL Server or Sybase Adaptive Server inputs MONEY data types as a numeric data type with a preceding dollar sign ($) as in the following example, select * from table_x where y > $5.00 You must remove the "$" sign from queries. Oracle is more general and works in international environments where the use of the "$" sign cannot be assumed. Support for other currency symbols and ISO standards through NLS is available in Oracle. |
|
NCHAR(n) |
Fixed-length character data type which uses the UNICODE UCS-2 character set. n must be a value in the range 1 to 4000. SQL Server or Sybase storage size is two times n. Note: Microsoft SQL Server or Sybase Adaptive Server storage size is two times n. SQL Developer maps columns sizes using byte semantics, and the size of Microsoft SQL Server or Sybase Adaptive Server NCHAR data types appear in the SQL Developer Source Model with "Size" specifying the number of bytes, as opposed to the number of Unicode characters. Thus, a SQL Server or Sybase column NCHAR(1000) will appear in the Source Model as NCHAR(2000). |
CHAR(n*2) |
|
|
NVARCHAR(n) |
Fixed-length character data type which uses the UNICODE UCS-2 character set. n must be a value in the range 1 to 4000. SQL Server or Sybase storage size is two times n. Note: Microsoft SQL Server or Sybase Adaptive Server storage size is two times n. SQL Developer maps columns sizes using byte semantics, and the size of Microsoft SQL Server NVARCHAR data types appear in the SQL Developer Source Model with "Size" specifying the number of bytes, as opposed to the number of Unicode characters. Thus, a SQL Server or Sybase column NVARCHAR(1000) will appear in the Source Model as NVARCHAR(2000). |
VARCHAR(n*2) |
|
|
SMALLMONEY |
Same as MONEY except monetary data values from -214,748.3648 to +214,748.3647, with accuracy to one ten-thousandth of a monetary unit. Storage size is 4 bytes. |
NUMBER(10,4) |
Since the range is -214,748.3648 to 214,748.364, NUMBER(10,4) suffices for this field. |
|
TIMESTAMP is defined as VARBINARY(8) with NULL allowed. Every time a row containing a TIMESTAMP column is updated or inserted, the TIMESTAMP column is automatically increment by the system. A TIMESTAMP column may not be updated by users. |
NUMBER |
You must place triggers on columns of this type to maintain them. In Oracle you can have multiple triggers of the same type without having to integrate them all into one big trigger. You may want to supply triggers to prevent updates of this column to enforce full compatibility. |
|
|
VARCHAR(30) in Microsoft SQL Server or Sybase Adaptive Server. NVARCHAR(128) in Microsoft SQL Server 7.0. |
VARCHAR2(30) and VARCHAR2(128) respectively. |
TEXT and IMAGE data types in Microsoft SQL Server or Sybase Adaptive Server follow these rules:
The column of these data types cannot be indexed.
The column cannot be a primary key.
The column cannot be used in the GROUP BY, ORDER BY, HAVING, and DISTINCT clauses.
IMAGE and TEXT data types can be referred to in the WHERE clause with the LIKE construct.
IMAGE and TEXT data types can also be used with the SUBSTR and LENGTH functions.
In Microsoft SQL Server or Sybase Adaptive Server, only columns with variable-length data types can store NULL values. When you create a column that allows NULLs with a fixed-length data type, the column is automatically converted to a system variable-length data type, as illustrated in Table 2-3. These variable-length data types are reserved system data types, and users cannot use them to create columns
Table 2-3 Data Type Conversion for NULL Values
| Fixed-Length Data Type | Variable-Length Data Type |
|---|---|
|
CHAR |
VARCHAR |
|
NCHAR |
NVARCHAR |
|
BINARY |
VARBINARY |
|
DATETIME, SMALLDATETIME |
DATETIMN |
|
FLOAT |
FLOATN |
|
INT, SMALLINT, TINYINT |
INTN |
|
DECIMAL |
DECIMALN |
|
NUMERIC |
NUMERICN |
|
MONEY, SMALLMONEY |
MONEYN |
Note:
The Oracle SQL Developer Source Model will display table system data types for each column.Recommendations
In addition to the data types listed in Table 2-2, users can define their own data types in Microsoft SQL Server or Sybase Adaptive Server databases. These user-defined data types translate to the base data types that are provided by the server. They do not allow users to store additional types of data, but can be useful in implementing standard data types for an entire application.
You can map data types from Microsoft SQL Server or Sybase Adaptive Server to Oracle with the equivalent data types listed in Table 2-3. SQL Developer converts user-defined data types to their base type. You can defined how the base type is mapped to an Oracle type in the Data Type Mappings page in the Options dialog.
This section provides a detailed description of the conceptual differences in data storage for the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases.
Specifically, it contains the following information:
A table (Table 2-4) comparing the data storage concepts of Microsoft SQL Server or Sybase Adaptive Server, and Oracle databases
Recommendations based on the information listed in the table
Table 2-4 Data Storage Concepts in Oracle and Microsoft SQL Server or Sybase Adaptive Server
Recommendations:
The conceptual differences in the storage structures do not affect the conversion process directly. However, the physical storage structures need to be in place before conversion of the database begins.
Oracle and Microsoft SQL Server or Sybase Adaptive Server have a way to control the physical placement of a database object. In Microsoft SQL Server or Sybase Adaptive Server, you use the ON SEGMENT clause and in Oracle you use the TABLESPACE clause.
An attempt should be made to preserve as much of the storage information as possible when converting from Microsoft SQL Server or Sybase Adaptive Server to Oracle. The decisions that were made when defining the storage of the database objects for Microsoft SQL Server or Sybase Adaptive Server should also apply for Oracle. Especially important are initial object sizes and physical object placement.
This section uses tables to compare the syntax and description of Data Manipulation Language (DML) elements in the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. Each table is followed by a recommendations section based on the information in the tables. The following topics are presented in this section:
The statement illustrated in Table 2-5 connects a user to a database.
Table 2-5 Connecting to the Database in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Syntax: USE database_name |
Syntax: CONNECT user_name/password SET role |
|
Description: A default database is assigned to each user. This database is made current when the user logs on to the server. A user executes the USE DATABASE_NAME command to switch to another database. |
Recommendations:
This concept of connecting to a database is conceptually different in the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. A Microsoft SQL Server or Sybase Adaptive Server user can log on to the server and switch to another database residing on the server, provided the user has privileges to access that database. An Oracle Server controls only one database, so here the concept of a user switching databases on a server does not exist. Instead, in Oracle a user executes the SET ROLE command to change roles or re-issues a CONNECT command using a different user_name.
The statement in Table 2-6 retrieves rows from one or more tables or views.
Table 2-6 SELECT Statements in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Syntax:
SELECT [ALL | DISTINCT] {select_list}
[INTO [owner.]table]
[FROM [owner.]{table | view}[alias] [HOLDLOCK]
[,[owner.]{table | view }[alias]
[HOLDLOCK]]...]
[WHERE condition]
[GROUP BY [ALL] aggregate_free_expression [, aggregate_free_expression]...]
[HAVING search_condition]
[UNION [ALL] SELECT...]
[ORDER BY {[[owner.]{table | view }.]column | select_list_number | expression}
[ASC | DESC]
[,{[[owner.]{table | view }.]column | select_list_number | expression}
[ASC | DESC]...]
[COMPUTE row_aggregate(column)
[,row_aggregate(column)...]
[BY column [, column...]]]
[FOR BROWSE]
The individual element in the select list is as follows:
[alias = ]
{* | [owner.]{table | view}.* | SELECT ... | {[owner.]table.column | constant_literal | expression}
[alias]}
|
Syntax:
SELECT [ALL | DISTINCT] {select_list}
FROM [user.]{table | view } [@dblink] [alias]
[, [user.] {table | view3} [@dblink] [alias]...
[WHERE condition]
[CONNECT BY condition [START WITH condition]]
[GROUP BY aggregate_free_expression
[,aggregate_free_expression]...]
[HAVING search_condition]
[ {UNION [ALL] | INTERSECT | MINUS} SELECT ...]
[ORDER BY {expression | position} [ASC | DESC]...]
[FOR UPDATE [OF [[user.]{table | view}.]column
[,[[user.]{table | view}.]column... ]
[noWAIT] ]
The individual element in the select list is as follows:
{ * | [owner.]{table | view | snapshot | synonym}.* | {[owner.]table.column | constant_literal | expression }
alias]}
|
|
Description: DISTINCT eliminates the duplicate rows. The INTO clause and the items that follow it in the command syntax are optional, because Microsoft SQL Server or Sybase Adaptive Server allows SELECT statements without FROM clauses as can be seen in the following example: SELECT getdate() SELECT...INTO allows you to insert the results of the SELECT statement into a table. SELECT_LIST can contain a SELECT statement in the place of a column specification as follows:
SELECT d.empno, d.deptname,
empname = (SELECT ename FROM emp
WHERE enum = d.empno)
FROM dept d
WHERE deptid = 10
The preceding example also shows the format for the column alias. ALIAS = selected_column COMPUTE attaches computed values at the end of the query. These are called row_aggregates. If a GROUP BY clause is used, all non-aggregate select columns are needed. FOR BROWSE keywords are used to get into browse mode. This mode supports the ability to perform updates while viewing data in an OLTP environment. It is used in front-end applications using DB-Library and a host programming language. Data consistency is maintained using the TIMESTAMP field in a multi-user environment. The selected rows are not locked; other users can view the same rows during the transaction. A user can update a row if the TIMESTAMP for the row is unchanged since the time of selection. |
Description: DISTINCT eliminates the duplicate rows. The INSERT INTO <table> SELECT FROM.... construct allows you to insert the results of the SELECT statement into a table. COLUMN ALIAS is defined by putting the alias directly after the selected COLUMN. If you use TABLE ALIAS, the TABLE must always be referenced using the ALIAS. You can also retrieve data from SYNONYMS. EXPRESSION could be a column name, a literal, a mathematical computation, a function, several functions combined, or one of several PSEUDO-COLUMNS. If a GROUP BY clause is used, all non-aggregate select columns must be in a GROUP BY clause. The FOR UPDATE clause locks the rows selected by the query. Other users cannot lock these row until you end the transaction. This clause is not a direct equivalent of the FOR BROWSE mode in Microsoft SQL Server or Sybase Adaptive Server. |
Microsoft SQL Server or Sybase Adaptive Server supports SELECT statements that do not have a FROM clause. This can be seen in the following example
SELECT getdate()
Oracle does not support SELECTs without FROM clauses. However, Oracle provides the DUAL table which always contains one row. Use the DUAL table to convert constructs such as the preceding one.
Translate the preceding query to:
SELECT sysdate FROM dual;
The Microsoft SQL Server or Sybase Adaptive Server SELECT INTO statement can insert rows into a table. This construct, which is part SELECT and part INSERT, is not supported by ANSI. Replace these statements with INSERT...SELECT statements in Oracle.
If the Microsoft SQL Server or Sybase Adaptive Server construct is similar to the following:
SELECT col1, col2, col3 INTO target_table FROM source_table WHERE where_clause
you should convert it to the following for Oracle:
INSERT into target_table SELECT col1, col2, col3 FROM source_table WHERE where_clause
Convert column aliases from the following Microsoft SQL Server or Sybase Adaptive Server syntax:
SELECT employees=col1 FROM tab1e
to the following Oracle syntax:
SELECT col1 employees FROM tab1e
Note:
Microsoft SQL Server or Sybase Adaptive Server also supports Oracle-style column aliases.Table 2-7 compares the SELECT with GROUP BY statement in Oracle to the same statement in Microsoft SQL Server or Sybase Adaptive Server.
Table 2-7 SELECT with GROUP BY Statement in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server/Server | Oracle |
|---|---|
|
Syntax: See the SELECT Statement section. |
Syntax: See the SELECT Statement section. |
|
Description: Non-aggregate SELECT columns must be in a GROUP BY clause. |
Description: All non-aggregate SELECT columns must be in a GROUP BY clause. |
The statements illustrated in the following table add one or more rows to the table or view.
Table 2-8 INSERT Statement in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Syntax:
INSERT [INTO] [[database.]owner.] {table | view}[(column [, column]...)]{VALUES (expression [,expression]...) | query}
|
Syntax:
INSERT INTO [user.]{table | view}[@dblink][(column [, column]...)]{VALUES (expression [, expression]...) | query...};
|
|
Description: INTO is optional. Inserts are allowed in a view provided only one of the base tables is undergoing change. |
Description: INTO is required. Inserts can only be done on single table views. |
Recommendations:
INSERT statements in Microsoft SQL Server or Sybase Adaptive Server must be changed to include an INTO clause if it is not specified in the original statement.
The values supplied in the VALUES clause in either database may contain functions. The Microsoft SQL Server or Sybase Adaptive Server-specific functions must be replaced with the equivalent Oracle constructs.
Note:
Oracle lets you create functions that directly match most Microsoft SQL Server or Sybase Adaptive Server functions.Convert inserts that are inserting into multi-table views in Microsoft SQL Server or Sybase Adaptive Server to insert directly into the underlying tables in Oracle.
The statement illustrated in Table 2-9 updates the data in a table or the data in a table referenced by a view.
Table 2-9 UPDATE Statement in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Syntax:
UPDATE [[database.]owner.] {table | view}
SET [[[database.]owner.] {table. | view.}]
column = expression | NULL | (select_statement)
[, column = expression | NULL | (select_statement)]...
[FROM [[database.]owner.]table | view
[, [[database.]owner.]table | view]...
[WHERE condition]
|
Syntax:
UPDATE [user.]{table | view} [@dblink]
SET [[ user.] {table. | view.}]
{ column = expression | NULL | (select_statement)
[, column = expression | NULL |
(select_statement)...] |
(column [, column]...) = (select_statement)}
[WHERE {condition | CURRENT OF cursor}]
|
|
Description: The FROM clause is used to get the data from one or more tables into the table that is being updated or to qualify the rows that are being updated. Updates through multi-table views can modify only columns in one of the underlying tables. |
Description: A single subquery may be used to update a set of columns. This subquery must select the same number of columns (with compatible data types) as are used in the list of columns in the SET clause. The Updates can only be done on single table views. |
Recommendations:
There are two ways to convert UPDATE statements with FROM clauses, as indicated in the following sections.
Use the subquery in the SET clause if columns are being updated to values coming from a different table.
Convert the following in Microsoft SQL Server or Sybase Adaptive Server:
update titles SET pub_id = publishers.pub_id FROM titles, publishers WHERE titles.title LIKE 'C%' AND publishers.pub_name = 'new age'
to the following in Oracle:
MERGE INTO titles USING (SELECT * FROM publishers) publishers ON ( titles.title LIKE 'C%' AND publishers.pub_name = 'new age' ) WHEN MATCHED THEN UPDATE SET pub_id = publishers.pub_id;
Use the subquery in the WHERE clause for all other UPDATE...FROM statements.
Convert the following in Microsoft SQL Server or Sybase Adaptive Server:
UPDATE shipping_parts SET qty = 0 FROM shipping_parts sp, suppliers s WHERE sp.supplier_num = s.supplier_num AND s.location = "USA"
to the following in Oracle:
MERGE INTO shipping_parts sp USING (SELECT * FROM suppliers) S ON ( sp.supplier_num = S.supplier_num AND S.location = 'USA' ) WHEN MATCHED THEN UPDATE SET qty = 0;
The statement illustrated in Table 2-10 removes rows from tables and rows from tables referenced in views.
Table 2-10 DELETE Statement in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Syntax:
DELETE [FROM] [[database.]owner.]{table | view}
[FROM [[database.]owner.]{table | view}
[, [[database.]owner.]{table | view}]...]
[WHERE where_clause]
|
Syntax:
DELETE [FROM] [user.]{table | view} [@dblink]
[alias]
[WHERE where_clause]
|
|
Description: The first FROM in DELETE FROM is optional. The second FROM clause is a Microsoft SQL Server or Sybase Adaptive Server extension that allows the user to make deletions based on the data in other tables. A subquery in the WHERE clause serves the same purpose. Deletes can only be performed through single table views. |
Description: FROM is optional. ALIAS can be specified for the table name as a correlation name, which can be used in the condition. Deletes can only be performed through single table views |
Remove the second FROM clause from the DELETE statements.
Convert the following Microsoft SQL Server or Sybase Adaptive Server query:
DELETE FROM sales FROM sales, titles WHERE sales.title_id = titles.title_id AND titles.type = 'business'
to the following in Oracle:
DELETE sales
WHERE ROWID IN
( SELECT sales.ROWID
FROM sales, titles
WHERE sales.title_id = titles.title_id
AND titles.TYPE = 'business' );
Remove the second FROM even if the WHERE contains a multi-column JOIN.
Convert the following Microsoft SQL Server or Sybase Adaptive Server query:
DELETE FROM sales FROM sales, table_x WHERE sales.a = table_x.a AND sales.b = table_x.b AND table_x.c = 'd'
to the following in Oracle:
DELETE sales
WHERE ROWID IN
( SELECT sales .ROWID
FROM sales ,
table_x
WHERE sales.a = table_x.a
AND sales.b = table_x.b
AND table_x.c = 'd' );
This section compares the different operators used in the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. It includes the following subsections:
Table 2-11 compares the operators used in the Microsoft SQL Serve, and Oracle databases. Comparison operators are used in WHERE clauses and COLUMN check constraints or rules to compare values.
Table 2-11 Comparison Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Operator | Same in Both Databases | Microsoft SQL Server or Sybase Adaptive Server Only | Oracle Only |
|---|---|---|---|
|
Equal to |
= |
||
|
Not equal to |
!= <> |
^= |
|
|
Less than |
< |
||
|
Greater than |
> |
||
|
Less than or equal to |
<= |
!> |
|
|
Greater than or equal to |
>= |
!< |
|
|
Greater than or equal to |
BETWEEN x AND y |
||
|
Less than |
NOT BETWEEN x AND y |
||
|
Pattern Matches
|
LIKE 'a%' LIKE 'a_' |
LIKE'a[x-z]' LIKE'a[^x-z]' |
LIKE 'a\%' ESCAPE '\' |
|
Does not match pattern |
NOT LIKE |
||
|
No value exists |
IS NULL |
||
|
A value exists |
IS NOT NULL |
||
|
At least one row returned by query |
EXISTS (query) |
||
|
No rows returned by query |
NOT EXISTS (query) |
||
|
Equal to a member of set |
IN =ANY |
= SOME |
|
|
Not equal to a member of set |
NOT IN != ANY <> ANY |
!= SOME <> SOME |
|
|
Less than a member of set |
< ANY |
< SOME |
|
|
Greater than a member of set |
> ANY |
> SOME |
|
|
Less than or equal to a member of set |
<= ANY |
!> ANY |
<= SOME |
|
Greater than or equal to a member of set |
>= ANY |
!< ANY |
>= SOME |
|
Equal to every member of set |
=ALL |
||
|
Not equal to every member of set |
!= ALL <> ALL |
||
|
Less than every member of set |
< ALL |
||
|
Greater than every member of set |
> ALL |
||
|
Less than or equal to every member of set |
<= ALL |
!> ALL |
|
|
Greater than or equal to every member of set |
>= ALL |
!< ALL |
Recommendations:
Convert all !< and !> to >= and <=
Convert the following in Microsoft SQL Server or Sybase Adaptive Server:
WHERE col1 !< 100
to this for Oracle:
WHERE col1 >= 100
Convert like comparisons which use [ ] and [^]
SELECT title FROM titles WHERE title like "[A-F]%"
Change NULL constructs:
Table 2-12 shows that in Oracle, NULL is never equal to NULL. Change the all = NULL constructs to IS NULL to retain the same functionality.
Table 2-12 Changing NULL Constructs
| NULL Construct | Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|---|
where col1 = NULL |
depends on the data |
FALSE |
where col1 != NULL |
depends on the data |
TRUE |
where col1 IS NULL |
depends on the data |
depends on the data |
where col1 IS NOT NULL |
depends on the data |
depends on the data |
where NULL = NULL |
TRUE |
FALSE |
If you have the following in Microsoft SQL Server or Sybase Adaptive Server:
WHERE col1 = NULL
Convert it as follows for Oracle:
WHERE col1 IS NULL
Table 2-13 Arithmetic Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Operator | Same in Both Databases | Microsoft SQL Server or Sybase Adaptive Server Only | Oracle Only |
|---|---|---|---|
|
Add |
+ |
||
|
Subtract |
- |
||
|
Multiply |
* |
||
|
Divide |
/ |
||
|
Modulo |
v |
% |
mod(x, y) |
Recommendations:
Replace any Modulo functions in Microsoft SQL Server or Sybase Adaptive Server with the mod() function in Oracle.
Table 2-14 String Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Operator | Same in Both Databases | Microsoft SQL Server or Sybase Adaptive Server Only | Oracle Only |
|---|---|---|---|
|
Concatenate |
s |
+ |
|| |
|
Identify Literal |
'this is a string' |
"this is also a string" |
Recommendations:
Replace all addition of strings with the || construct.
Replace all double quotes string identifiers with single quote identifiers.
In Microsoft SQL Server or Sybase Adaptive Server, an empty string ('') is interpreted as a single space in INSERT or assignment statements on VARCHAR data. In concatenating VARCHAR, CHAR, or TEXT data, the empty string is interpreted as a single space. The empty string is never evaluated as NULL. You must bear this in mind when converting the application.
Table 2-15 Set Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Operator | Same in Both Databases | Microsoft SQL Server or Sybase Adaptive Server Only | Oracle Only |
|---|---|---|---|
|
Distinct row from either query |
UNION |
||
|
All rows from both queries |
UNION ALL |
||
|
All distinct rows in both queries |
d |
INTERSECT |
|
|
All distinct rows in the first query but not in the second query |
d |
MINUS |
Table 2-16 Bit Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Operator | Same in Both Databases | Microsoft SQL Server or Sybase Adaptive Server Only | Oracle Only |
|---|---|---|---|
|
bit and |
& |
||
|
bit or |
| |
||
|
bit exclusive or |
^ |
||
|
bit not |
~ |
Recommendations:
Oracle enables you to write the procedures to perform bitwise operations.
If you have the following Microsoft SQL Server or Sybase Adaptive Server construct:
X | Y :(Bitwise OR)
You could write a procedure called dbms_bits.or (x,y) and convert the preceding construct to the following in Oracle:
dbms_bits.or(x,y)
This section compares the different functions used in the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. It includes the following subsections:
Table 2-17 Character Functions in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle | Description |
|---|---|---|
|
ascii(char) |
ascii(char) |
Returns the ASCII equivalent of the character. |
|
char(integer_expression) |
chr(integer_expression) |
Converts the decimal code for an ASCII character to the corresponding character. |
|
charindex(specified_exp, char_string) |
instr(specified_exp, char_string, 1, 1) |
Returns the position where the specified_exp first occurs in the char_string. |
|
convert(data type, expression, [format]) |
to_char, to_number, to_date, to_label, chartorowid, rowtochar, hextochar, chartohex |
Converts one data type to another using the optional format. The majority of the functionality can be matched. Refer to Oracle Database SQL Language Reference for more information. |
|
datalength(expression) |
g |
Computes the length allocated to an expression, giving the result in bytes. |
|
difference(character_exp, character_exp) |
d |
Returns the numeric difference of the SOUNDEX values of the two strings. |
|
isnull(variable, new_value) |
nvl(variable, new_value) |
If the value of the variable is NULL, the new_value is returned. |
|
lower(char_exp) |
lower(char_exp) |
Converts uppercase characters to lowercase characters. |
|
ltrim(char_exp) |
ltrim(char_exp) |
Truncates trailing spaces from the left end of char_exp. |
|
patindex(pattern, |
column_name) |
Returns the position of the pattern in the column value. The pattern can have wild characters. This function also works on TEXT and BINARY data types. |
|
replicate(char_exp, n) |
rpad(char_exp, length(char_exp)*n, '') |
Produces a string with char_exp repeated n times. |
|
reverse(char_string) |
Reverses the given |
|
|
right(char_exp, n) |
substr(char_exp, (length(char_exp) |
Returns the part of the string starting at the position given by n from the right and extending up to the end of the string. |
|
rtrim(char_exp) |
rtrim(char_exp) |
Truncates the trailing spaces from the right end of char_exp. |
|
soundex(exp) |
soundex(exp) |
Returns phonetically similar expressions to the specified exp. |
|
space(int_exp) |
rpad(' ', int_exp-1, '') |
Generates a string with int_exp spaces. |
|
str(float_exp, length) |
to_char(float_exp)stuff(char_exp, start, length, replace_str)substr(char_exp, 1, start) ||replace_str ||substr(char_exp, start+length) |
Replaces a substring within char_exp with replace_str. |
|
substring(char_exp, start, length) Works on IMAGE and TEXT data types |
substr(char_exp, start, length) Does not work with LONG and LONG_RAW data types |
Replaces a substring within char_exp with replace_str. |
|
textptr(column_name) |
d |
Returns a pointer as a varbinary(16) data type for a named IMAGE or TEXT column. |
|
textvalid("column_name", text_pointer) |
h |
Returns 1 if the specified text_pointer is valid for the specified column_name. The column must be of type TEXT or IMAGE. |
|
upper(char_exp) |
upper(char_exp) |
Converts lowercase characters to uppercase characters. |
Table 2-18 Comparison Operators in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle | Description |
|---|---|---|
|
datalength(expression) |
lengthb |
Computes the length allocated to an expression, giving the result in bytes. |
|
isnull(variable, new_value) |
nvl(variable, new_value) |
If the value of the variable is NULL, the new_value is returned. |
Note:
The preceding functions tables list all the Microsoft SQL Server or Sybase Adaptive Server character manipulation functions. They do not list all the Oracle functions. There are many more Oracle character manipulation functions that you can use.Table 2-19 Date Functions in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle | Description |
|---|---|---|
dateadd(dd, int_exp,datetime_var) |
date+int_exp requires conversion of int_exp to a number of days |
Adds the int_exp number of days to the date contained in datetime_var. |
dateadd(mm, int_exp,datetime_var) |
add_months(date, int_exp) or date+int_exp requires conversion of int_exp to a number of days |
Adds the int_exp number of months to the date contained in datetime_var. |
dateadd(yy, int_exp,datetime_var) |
date+int_exp requires conversion of int_exp to a number of days |
Adds the int_exp number of years to the date contained in datetime_var. |
datediff(dd, datetime1,datetime2) |
date2-date1 |
Returns the difference between the dates specified by the datetime1 and datetime2 variables. This difference is calculated in the number of days. |
datediff(mm, datetime1,datetime2) |
months_between (date2, date1) |
Returns the difference between the dates specified by the datetime1 and datetime2 variables. This difference is calculated in the number of months. |
datediff(yy, datetime1,datetime2) |
(date2-date1) /365.254 |
Returns the difference between the dates specified by the datetime1 and datetime2 variables. This difference is calculated in the number of years. |
datename (datepart, date) |
to_char(date, format) |
Returns the specified part of the date as an integer. The Microsoft SQL Server or Sybase Adaptive Server DATETIME has a higher precision than Oracle DATE. For this reason, it is not always possible to find an equivalent format string in Oracle to match the datepart in Microsoft SQL Server or Sybase Adaptive Server. See the Data Types section of this chapter for more information about conversion of the DATETIME data type. |
datepart(datepart, date) |
to_char(date, format) |
Returns the specified part of the date as a character string (name). The Microsoft SQL Server or Sybase Adaptive Server DATETIME has a higher precision than Oracle DATE'. For this reason, it is not always possible to find an equivalent format string in Oracle to match the datepart in Microsoft SQL Server or Sybase Adaptive Server. |
getdate() |
sysdate |
Returns the system date. |
Recommendations:
The preceding table lists all the Microsoft SQL Server or Sybase Adaptive Server date manipulation functions. It does not list all the Oracle date functions. There are many more Oracle date manipulation functions that you can use.
It is recommended that you convert most date manipulation functions to "+" or "-" in Oracle.
Oracle adds the ability to define functions. With this feature you can create Oracle functions that match the name and functionality of all Microsoft SQL Server or Sybase Adaptive Server functions. This is a useful feature, where users can call a PL/SQL function from a SQL statement's SELECT LIST, WHERE clause, ORDER BY clause, and HAVING clause. With the parallel query option, Oracle executes the PL/SQL function in parallel with the SQL statement. Hence, users create parallel logic.
Table 2-20 Mathematical Functions in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
abs(n) |
abs(n) |
|
acos(n) |
acos(n) |
|
asin(n) |
|
|
atan(n) |
atan(n) |
|
atn2(n,m) |
|
|
ceiling(n) |
ceil(n) |
|
cos(n) |
cos(n) |
|
cot(n) |
|
|
degrees(n) |
|
|
exp(n) |
exp(n) |
|
floor(n) |
floor(n) |
|
log(n) |
ln(n) |
|
log10(n) |
log(base,number) |
|
pi() |
|
|
power(m,n) |
power(m,n) |
|
radians(n) |
|
|
rand(n) |
|
|
round(n[,m]) |
round(n[,m]) |
|
sign(n) |
sign(n) |
|
sin(n) |
sin(n) |
|
sqrt(n) |
sqrt(n) |
|
tan(n) |
tan(n) |
Recommendations:
The preceding table lists all the Microsoft SQL Server or Sybase Adaptive Server number manipulation functions. It does not list all the Oracle mathematical functions. There are many more Oracle number manipulation functions that you can use.
Oracle adds the ability to define functions. With this feature you can create Oracle functions that match the name and functionality of all Microsoft SQL Server or Sybase Adaptive Server functions. This is the most flexible approach. Users can write their own functions and execute them seamlessly from a SQL statement.
Oracle functions listed in the table work in SQL as well as PL/SQL.
This section compares locking and transaction handling in the Microsoft SQL Server or Sybase Adaptive Server and Oracle databases. It includes the following subsections:
Locking serves as a control mechanism for concurrency. Locking is a necessity in a multi-user environment because more than one user at a time may be working with the same data.
Table 2-21 Locking in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Microsoft SQL Server or Sybase Adaptive Server locking is fully automatic and does not require intervention by users. Microsoft SQL Server or Sybase Adaptive Server applies exclusive locks for INSERT, UPDATE, and DELETE operations. When an exclusive lock is set, no other transaction can obtain any type of lock on those objects until the original lock is in place. For non-update or read operations, a shared lock is applied. If a shared lock is applied to a table or a page, other transactions can also obtain a shared lock on that table or page. However, no transaction can obtain an exclusive lock. Therefore, Microsoft SQL Server or Sybase Adaptive Server reads block the modifications to the data. Update locks: Update locks are held at the page level. They are placed during the initial stages of an update operation when the pages are being read. Update locks can co-exist with shared locks. If the pages are changed later, the update locks are escalated to exclusive locks. |
Oracle locking is fully automatic and does not require intervention by users. Oracle features the following categories of locks: Data locks (DML locks) to protect data.The "table locks" lock the entire table and "row locks" lock individual rows. Dictionary locks (DDL locks) to protect the structure of objects. Internal locks to protect internal structures, such as files. DML operations can acquire data locks at two different levels; one for specific rows and one for entire tables. Row-level locks: An exclusive lock is acquired for an individual row on behalf of a transaction when the row is modified by a DML statement. If a transaction obtains a row level lock, it also acquires a table (dictionary) lock for the corresponding table. This prevents conflicting DDL (DROP TABLE, ALTER TABLE) operations that would override data modifications in an on-going transaction. |
|
Intent locks: Microsoft SQL Server or Sybase Adaptive Server locking is fully automatic and does not require intervention by users. Microsoft SQL Server or Sybase Adaptive Server applies exclusive locks for INSERT, UPDATE, and DELETE operations. When an exclusive lock is set, no other transaction can obtain any type of lock on those objects until the original lock is in place. For non-update or read operations, a shared lock is applied. If a shared lock is applied to a table or a page, other transactions can also obtain a shared lock on that table or page. However, no transaction can obtain an exclusive lock. Therefore, Microsoft SQL Server or Sybase Adaptive Server reads block the modifications to the data. Extent locks: Extent locks lock a group of eight database pages while they are being allocated or freed. These locks are held during a CREATE or DROP statement, or during an INSERT that requires new data or index pages. A list of active locks for the current server can be seen with SP_LOCK system procedure. |
Table-level data locks can be held in any of the following modes: Row share table lock (RW): This indicates that the transaction holding the lock on the table has locked rows in the table and intends to update them. This prevents other transactions from obtaining exclusive write access to the same table by using the LOCK TABLE table IN EXCLUSIVE MODE statement. Apart from that, all the queries, inserts, deletes, and updates are allowed in that table. Row exclusive table lock (RX): This generally indicates that the transaction holding the lock has made one or more updates to the rows in the table. Queries, inserts, deletes, updates are allowed in that table. Share lock (SL): Share row exclusive lock(SRX) Exclusive lock (X): The dynamic performance table V$LOCK keeps the information about locks. |
Recommendations:
In Microsoft SQL Server or Sybase Adaptive Server, SELECT statements obtain shared locks on pages/rows. This prevents other statements from obtaining an exclusive lock on those pages/rows. All statements that update the data need an exclusive lock. This means that the SELECT statement in Microsoft SQL Server or Sybase Adaptive Server blocks the UPDATE statements as long as the transaction that includes the SELECT statement does not commit or rollback. This also means that two transactions are physically serialized whenever one transaction selects the data and the other transaction wants to change the data first and then select the data again. In Oracle, however, SELECT statements do not block UPDATE statements, since the rollback segments are used to store the changed data before it is updated in the actual tables. Also, the reader of the data is never blocked in Oracle. This allows Oracle transactions to be executed simultaneously.
If Microsoft SQL Server or Sybase Adaptive Server logical transactions are automatically translated to Oracle logical transactions, the preceding transactions that execute properly in Microsoft SQL Server or Sybase Adaptive Server as they are serialized cause a deadlock in Oracle. These transactions should be identified and serialized to avoid the deadlock. These transactions are serialized in Microsoft SQL Server or Sybase Adaptive Server as INSERT, UPDATE, and DELETE statements block other statements.
Table 2-22 Row-Level Versus Page-Level Locking in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Microsoft SQL Server or Sybase Adaptive Server does not have a row-level locking feature. Microsoft SQL Server or Sybase Adaptive Server applies a page-level lock, which effectively locks all rows on the page, whenever any row in the page is being updated. This is an exclusive lock whenever the data is being changed by DML statements. Microsoft SQL Server 7.0 implements a form of row-level locking. Microsoft SQL Server 7.0 escalates locks at row level to page level automatically. SELECT statements are blocked by exclusive locks that lock an entire page. |
Oracle has a row-locking feature. Only one row is locked when a DML statement is changing the row. |
Recommendations:
No changes are required to take advantage of the row-level locking feature of Oracle.
Table 2-23 Read Consistency in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
Microsoft SQL Server or Sybase Adaptive Server provides the HOLDLOCK function for transaction-level read consistency. Specifying a SELECT with HOLDLOCK puts a shared lock on the data. More than one user can execute a SELECT with HOLDLOCK at the same time without blocking each other. When one of the users tries to update the selected data, HOLDLOCK blocks the update until the other users commit, rollback, or attempt an update and a deadlock occurs. This means that HOLDLOCK prevents other transactions from updating the same data until the current transaction is in effect. |
Read consistency as supported by Oracle does the following:
To provide read consistency, Oracle creates a read-consistent set of data when a table is being read and simultaneously updated. Read consistency functions as follows:
You can specify that a transaction be read only using the following command: SET TRANSACTION READ ONLY |
Table 2-24 Logical Transaction Handling in Oracle and Microsoft SQL Server or Sybase Adaptive Server
| Microsoft SQL Server or Sybase Adaptive Server | Oracle |
|---|---|
|
After completion, any statement not within a transaction is automatically committed.A statement can be a batch containing multiple T-SQL statements that are sent to the server as one stream. The changes to the database are automatically committed after the batch executes. A ROLLBACK TRAN statement subsequently executed has no effect. In Microsoft SQL Server or Sybase Adaptive Server, transactions are not implicit. Start logical transaction with a BEGIN TRANSACTION clause. Logical transactions can be committed or rolled back as follows. BEGIN TRANSACTION [transaction_name] Use COMMIT TRAN to commit the transaction to the database. You have the option to specify the transaction name. Use ROLLBACK TRAN to roll back the transaction. You can set savepoints to roll back to a certain point in the logical transaction using the following command: SAVE TRANSACTION savepoint_name Roll back to the specified SAVEPOINT with the following command: ROLLBACK TRAN <savepoint_name> |
Statements are not automatically committed to the database. The COMMIT WORK statement is required to commit the pending changes to the database. Oracle transactions are implicit. This means that the logical transaction starts as soon as data changes in the database. COMMIT WORK commits the pending changes to the database. ROLLBACK undoes all the transactions after the last COMMIT WORK statement. Savepoints can be set in transactions with the following command: SET SAVEPOINT savepoint_name The following command rolls back to the specified SAVEPOINT: ROLLBACK <savepoint_name> Two-phase commit is automatic and transparent in Oracle. Two-phase commit operations are needed only for transactions which modify data on two or more databases. |
|
Microsoft SQL Server or Sybase Adaptive Server allows you to nest BEGIN TRAN/COMMIT TRAN statements. When nested, the outermost pair of transactions creates and commits the transaction. The inner pairs keep track of the nesting levels. A ROLLBACK command in the nested transactions rolls back to the outermost BEGIN TRAN level, if it does not include the name of the SAVEPOINT. Most Microsoft SQL Server or Sybase Adaptive Server applications require two-phase commit, even on a single server. To see if the server is prepared to commit the transaction, use PREPARE TRAN in two-phase commit applications. Completed transactions are written to the database device at CHECKPOINT. A CHECKPOINT writes all dirty pages to the disk devices since the last CHECKPOINT. Calls to remote procedures are executed independently of any transaction in which they are included. |
When a CHECKPOINT occurs, the completed transactions are written to the database device. A CHECKPOINT writes all dirty pages to the disk devices that have been modified since last checkpoint |
Recommendations:
Transactions are not implicit in Microsoft SQL Server or Sybase Adaptive Server. Therefore, applications expect that every statement they issue is automatically committed it is executed.
Oracle transactions are always implicit, which means that individual statements are not committed automatically. When converting a Microsoft SQL Server or Sybase Adaptive Server application to an Oracle application, care needs to be taken to determine what constitutes a transaction in that application. In general, a COMMIT work statement needs to be issued after every "batch" of statements, single statement, or stored procedure call to replicate the behavior of Microsoft SQL Server or Sybase Adaptive Server for the application.
In Microsoft SQL Server or Sybase Adaptive Server, transactions may also be explicitly begun by a client application by issuing a BEGIN TRAN statement during the conversion process.