For working with character data, Firebird has the fixed-length CHAR and the variable-length VARCHAR data types. The maximum size of text data stored in these data types is 32, bytes for CHAR and 32, bytes for VARCHAR. The maximum number of characters that will fit within these limits depends on the CHARACTER SET being used for the data under consideration.

The collation sequence does not affect this maximum, although it may affect the maximum size of any index that involves the column. If no character set is explicitly specified when defining a character object, the default character set specified when the database was created will be used.

If the database does not have a default character set defined, the field gets the character set NONE. UTF8 comes with collations for many languages. Non-accented Latin letters occupy 1 byte, Cyrillic letters from the WIN encoding occupy 2 bytes in UTF8 , characters from other encodings may occupy up to 4 bytes. The UTF8 character set implemented in Firebird supports the latest version of the Unicode standard, thus recommending its use for international databases.

While working with strings, it is essential to keep the character set of the client connection in mind. If there is a mismatch between the character sets of the stored data and that of the client connection, the output results for string columns are automatically re-encoded, both when data are sent from the client to the server and when they are sent back from the server to the client. The character set NONE is a special character set in Firebird. It can be characterized such that each byte is a part of a string, but the string is stored in the system without any clues about what constitutes any character: character encoding, collation, case, etc.

are simply unknown. It is the responsibility of the client application to deal with the data and provide the means to interpret the string of bytes in some way that is meaningful to the application and the human user. Data in OCTETS encoding are treated as bytes that may not actually be interpreted as characters.

OCTETS provides a way to store binary data, which could be the results of some Firebird functions. The database engine has no concept of what it is meant to do with a string of bits in OCTETS , other than just store it and retrieve it.

Again, the client side is responsible for validating the data, presenting them in formats that are meaningful to the application and its users and handling any exceptions arising from decoding and encoding them. Each character set has a default collation sequence COLLATE that specifies the collation order. Usually, it provides nothing more than ordering based on the numeric code of the characters and a basic mapping of upper- and lower-case characters. If some behaviour is needed for strings that is not provided by the default collation sequence and a suitable alternative collation is supported for that character set, a COLLATE collation clause can be specified in the column definition.

A COLLATE collation clause can be applied in other contexts besides the column definition. If output needs to be sorted in a special alphabetic sequence, or case-insensitively, and the appropriate collation exists, then a COLLATE clause can be included with the ORDER BY clause when rows are being sorted on a character field and with the GROUP BY clause in case of grouping operations.

For a case-insensitive search, the UPPER function could be used to convert both the search argument and the searched strings to upper-case before attempting a match:. For strings in a character set that has a case-insensitive collation available, you can simply apply the collation, to compare the search argument and the searched strings directly. The following table shows the possible collation sequences for the UTF8 character set.

Collation works according to the position of the character in the table binary. Added in Firebird 2. Collation works according to the UCA algorithm Unicode Collation Algorithm alphabetical. Case-insensitive collation, works without taking character case into account. Case-insensitive, accent-insensitive collation, works alphabetically without taking character case or accents into account.

In Firebird earlier than version 2. Multi-byte character sets and compound indexes limit the size even further. The maximum length of an indexed string is 9 bytes less than that quarter-page limit. The table below shows the maximum length of an indexed string in characters , according to page size and character set, calculated using this formula.

CREATE DATABASE , Collation sequence , SELECT , WHERE , GROUP BY , ORDER BY. CHAR is a fixed-length data type. If the entered number of characters is less than the declared length, trailing spaces will be added to the field. Generally, the pad character does not have to be a space: it depends on the character set. For example, the pad character for the OCTETS character set is zero.

The full name of this data type is CHARACTER , but there is no requirement to use full names and people rarely do so. A valid length is from 1 to the maximum number of characters that can be accommodated within 32, bytes. VARCHAR is the basic string type for storing texts of variable length, up to a maximum of 32, bytes.

The stored structure is equal to the actual size of the data plus 2 bytes where the length of the data is recorded. All characters that are sent from the client application to the database are considered meaningful, including the leading and trailing spaces. However, trailing spaces are not stored: they will be restored upon retrieval, up to the recorded length of the string. The full name of this type is CHARACTER VARYING.

Another variant of the name is written as CHAR VARYING. In all other respects it is the same as CHAR. A similar data type is available for the variable-length string type: NATIONAL CHARACTER VARYING.

BLOB s Binary Large Objects are complex structures used to store text and binary data of an undefined length, often very large. Specifying the BLOB segment is throwback to times past, when applications for working with BLOB data were written in C Embedded SQL with the help of the gpre pre-compiler. Nowadays, it is effectively irrelevant. The segment size for BLOB data is determined by the client side and is usually larger than the data page size, in any case.

Firebird provides two pre-defined subtypes for storing user data:. The alias for subtype zero is BINARY. This is the subtype to specify when the data are any form of binary file or stream: images, audio, word-processor files, PDFs and so on. Subtype 1 has an alias, TEXT , which can be used in declarations and definitions.

It is a specialized subtype used to store plain text data that is too large to fit into a string type. A CHARACTER SET may be specified, if the field is to store text with a different encoding to that specified for the database. From Firebird 2. It is also possible to add custom data subtypes, for which the range of enumeration from -1 to , is reserved. Custom subtypes enumerated with positive numbers are not allowed, as the Firebird engine uses the numbers from 2-upward for some internal subtypes in metadata.

The maximum size of a BLOB field is limited to 4GB, regardless of whether the server is bit or bit. The internal structures related to BLOB s maintain their own 4-byte counters. The following operators are supported completely:. Aggregation clauses work not on the contents of the field itself, but on the BLOB ID. Aside from that, there are some quirks:. concatenates the same strings if they are adjacent to each other, but does not do it if they are remote from each other.

By default, a regular record is created for each BLOB and it is stored on a data page that is allocated for it. If the entire BLOB fits onto this page, it is called a level 0 BLOB. The number of this special record is stored in the table record and occupies 8 bytes.

If a BLOB does not fit onto one data page, its contents are put onto separate pages allocated exclusively to it blob pages , while the numbers of these pages are stored into the BLOB record. This is a level 1 BLOB. If the array of page numbers containing the BLOB data does not fit onto a data page, the array is put on separate blob pages, while the numbers of these pages are put into the BLOB record.

This is a level 2 BLOB. FILTER , DECLARE FILTER. The support of arrays in the Firebird DBMS is a departure from the traditional relational model. Supporting arrays in the DBMS could make it easier to solve some data-processing tasks involving large sets of similar data. Arrays in Firebird are stored in BLOB of a specialized type.

Arrays can be one-dimensional and multidimensional and of any data type except BLOB and ARRAY. This example will create a table with a field of the array type consisting of four integers. The subscripts of this array are from 1 to 4. To specify explicit upper and lower bounds of the subscript values, use the following syntax:. A new dimension is added using a comma in the syntax. In this example we create a table with a two-dimensional array, with the lower bound of subscripts in both dimensions starting from zero:.

The DBMS does not offer much in the way of language or tools for working with the contents of arrays. The database employee. fdb , found in the.. If the features described are enough for your tasks, you might consider using arrays in your projects. Currently, no improvements are planned to enhance support for arrays in Firebird.

It is not available as a data type for declaring table fields, PSQL variables or parameter descriptions. It was added to support the use of untyped parameters in expressions involving the IS NULL predicate. An evaluation problem occurs when optional filters are used to write queries of the following type:. This is a case where the developer writes an SQL query and considers :param1 as though it were a variable that he can refer to twice.

The server cannot determine the type of the second parameter since it comes in association with IS NULL. The following example demonstrates its use in practice. Each named parameter corresponds with two positional parameters in the query.

The application passes the parameterized query to the server in the usual positional? in our example. Firebird has no knowledge of their special relation with the first and third parameters: that responsibility lies entirely on the application side.

Once the values for size and colour have been set or left unset by the user and the query is about to be executed, each pair of XSQLVAR s must be filled as follows:. In other words: The value compare parameter is always set as usual. When composing an expression or specifying an operation, the aim should be to use compatible data types for the operands.

When a need arises to use a mixture of data types, it should prompt you to look for a way to convert incompatible operands before subjecting them to the operation. The ability to convert data may well be an issue if you are working with Dialect 1 data. When you cast to a domain, any constraints declared for it are taken into account, i. If the value does not pass the check, the cast will fail. When operands are cast to the type of a column, the specified column may be from a table or a view.

Only the type of the column itself is used. For character types, the cast includes the character set, but not the collation. The constraints and default values of the source column are not applied. Keep in mind that partial information loss is possible. For instance, when you cast the TIMESTAMP data type to the DATE data type, the time-part is lost.

To cast string data types to the DATE , TIME or TIMESTAMP data types, you need the string argument to be one of the predefined date and time literals see Table 9 or a representation of the date in one of the allowed date-time literal formats:. It may contain 1 or 2 digits or You can also specify the three-letter shorthand name or the full name of a month in English.

A separator, any of permitted characters. Leading and trailing spaces are ignored. These shorthand expressions are evaluated directly during parsing, as though the statement were already prepared for execution. Thus, even if the query is run several times, the value of, for instance, timestamp 'now' remains the same no matter how much time passes.

If you need the time to be evaluated at each execution, use the full CAST syntax. An example of using such an expression in a trigger:. In Dialect 1, in many expressions, one type is implicitly cast to another without the need to use the CAST function. For instance, the following statement in Dialect 1 is valid:.

In Dialect 1, mixing integer data and numeric strings is usually possible because the parser will try to cast the string implicitly. For example,. In Dialect 3, an expression like this will raise an error, so you will need to write it as a CAST expression:.

When multiple data elements are being concatenated, all non-string data will undergo implicit conversion to string, if possible. Creating a domain does not truly create a new data type, of course. If several tables need columns defined with identical or nearly identical attributes, a domain makes sense. Domain usage is not limited to column definitions for tables and views. Domains can be used to declare input and output parameters and variables in PSQL code.

A domain definition contains required and optional attributes. The data type is a required attribute. Optional attributes include:. Explicit Data Type Conversion for the description of differences in the data conversion mechanism when domains are specified for the TYPE OF and TYPE OF COLUMN modifiers. While defining a column using a domain, it is possible to override some of the attributes inherited from the domain. Table 3. To add new conditions to the check, you can use the corresponding CHECK clauses in the CREATE and ALTER statements at the table level.

Often it is better to leave domain nullable in its definition and decide whether to make it NOT NULL when using the domain to define columns. CREATE DOMAIN in the Data Definition Language DDL section. To change the attributes of a domain, use the DDL statement ALTER DOMAIN. With this statement you can:. If you change domains in haste, without carefully checking them, your code may stop working! When you convert data types in a domain, you must not perform any conversions that may result in data loss.

Also, for example, if you convert VARCHAR to INTEGER , check carefully that all data using this domain can be successfully converted. ALTER DOMAIN in the Data Definition Language DDL section.

The DDL statement DROP DOMAIN deletes a domain from the database, provided it is not in use by any other database objects. DROP DOMAIN in the Data Definition Language DDL section. SQL expressions provide formal methods for evaluating, transforming and comparing values. SQL expressions may include table columns, variables, constants, literals, various statements and predicates and also other expressions.

The complete list of possible tokens in expressions follows. Identifier of a column from a specified table used in evaluations or as a search condition. A column of the array type cannot be an element in an expression except when used with the IS [NOT] NULL predicate. An expression may contain a reference to an array member i. The reserved words NOT , AND and OR , used to combine simple search conditions in order to create complex assertions.

Predicates used to check the existence of values in a set. The IN predicate can be used both with sets of comma-separated constants and with subqueries that return a single column. The EXISTS , SINGULAR , ALL , ANY and SOME predicates can be used only with subqueries. An expression, similar to a string literal enclosed in apostrophes, that can be interpreted as a date, time or timestamp value.

Date literals can be predefined literals 'TODAY' , 'NOW' , etc. or strings of characters and numerals, such as ' Declared local variable, input or output parameter of a PSQL module stored procedure, trigger, unnamed PSQL block in DSQL. A member of in an ordered group of one or more unnamed parameters passed to a stored procedure or prepared query. A SELECT statement enclosed in parentheses that returns a single scalar value or, when used in existential predicates, a set of values.

Operations inside the parentheses are performed before operations outside them. When nested parentheses are used, the most deeply nested expressions are evaluated first and then the evaluations move outward through the levels of nesting. Clause applied to CHAR and VARCHAR types to specify the character-set-specific collation sequence to use in string comparisons. Expression for obtaining the next value of a specified generator sequence. A constant is a value that is supplied directly in an SQL statement, not derived from an expression, a parameter, a column reference nor a variable.

It can be a string or a number. The maximum length of a string is 32, bytes; the maximum character count will be determined by the number of bytes used to encode each character. Double quotes are NOT VALID for quoting strings. SQL reserves a different purpose for them. Care should be taken with the string length if the value is to be written to a VARCHAR column.

The maximum length for a VARCHAR is 32, bytes. The character set of a string constant is assumed to be the same as the character set of its destined storage. Each pair of hex digits defines one byte in the string. Strings entered this way will have character set OCTETS by default, but the introducer syntax can be used to force a string to be interpreted as another character set. The client interface determines how binary strings are displayed to the user.

The isql utility, for example, uses upper case letters A-F, while FlameRobin uses lower case letters. Other client programs may use other conventions, such as displaying spaces between the byte pairs: '4E 65 72 76 65 6E'.

The hexadecimal notation allows any byte value including 00 to be inserted at any position in the string. However, if you want to coerce it to anything other than OCTETS, it is your responsibility to supply the bytes in a sequence that is valid for the target character set. This is known as introducer syntax. Its purpose is to inform the engine about how to interpret and store the incoming string. In SQL, for numbers in the standard decimal notation, the decimal point is always represented by period.

Inclusion of commas, blanks, etc. will cause errors. Exponential notation is supported. For example, 0. Hexadecimal notation is supported by Firebird 2.

Numbers with hex digits will be interpreted as type INTEGER ; numbers with hex digits as type BIGINT. Hex numbers in the range To coerce a number to BIGINT , prepend enough zeroes to bring the total number of hex digits to nine or above. That changes the type but not the value. When written with eight hex digits, as in 0x9E44F9A8 , a value is interpreted as bit INTEGER. Since the leftmost bit sign bit is set, it maps to the negative range With one or more zeroes prepended, as in 0x09E44F9A8 , a value is interpreted as bit BIGINT in the range The sign bit is not set now, so they map to the positive range This is something to be aware of.

Hex numbers between FFFF FFFF FFFF FFFF are all negative BIGINT. A SMALLINT cannot be written in hex, strictly speaking, since even 0x1 is evaluated as INTEGER.

However, if you write a positive integer within the bit range 0x decimal zero to 0x7FFF decimal it will be converted to SMALLINT transparently.

It is possible to write to a negative SMALLINT in hex, using a 4-byte hex number within the range 0xFFFF decimal to 0xFFFFFFFF decimal SQL operators comprise operators for comparing, calculating, evaluating and concatenating values. SQL Operators are divided into four types. Each operator type has a precedence , a ranking that determines the order in which operators and the values obtained with their help are evaluated in an expression. The higher the precedence of the operator type is, the earlier it will be evaluated.

Each operator has its own precedence within its type, that determines the order in which they are evaluated in an expression. Operators with the same precedence are evaluated from left to right. To force a different evaluation order, operations can be grouped by means of parentheses. Arithmetic operations are performed after strings are concatenated, but before comparison and logical operations. Comparison operations take place after string concatenation and arithmetic operations, but before logical operations.

Character strings can be constants or values obtained from columns or other expressions. Combines two or more predicates, each of which must be true for the entire predicate to be true. Combines two or more predicates, of which at least one predicate must be true for the entire predicate to be true. NEXT VALUE FOR returns the next value of a sequence. SEQUENCE is an SQL-compliant term for a generator in Firebird and its ancestor, InterBase.

A step value of 0 returns the current sequence value. A conditional expression is one that returns different values according to how a certain condition is met. It is composed by applying a conditional function construct, of which Firebird supports several.

This section describes only one conditional expression construct: CASE. All other conditional expressions apply internal functions derived from CASE and are described in Conditional Functions. The CASE construct returns a single value from a number of possible ones. Two syntactic variants are supported:. The simple CASE , comparable to a case construct in Pascal or a switch in C. When this variant is used, test-expr is compared expr 1, expr 2 etc.

If no match is found, defaultresult from the optional ELSE clause is returned. If there are no matches and no ELSE clause, NULL is returned. That is, if test-expr is NULL , it does not match any expr , not even an expression that resolves to NULL.

The returned result does not have to be a literal value: it might be a field or variable name, compound expression or NULL literal. A short form of the simple CASE construct is the DECODE function. The first expression to return TRUE determines the result. If no expressions return TRUE , defaultresult from the optional ELSE clause is returned as the result.

If no expressions return TRUE and there is no ELSE clause, the result will be NULL. As with the simple CASE construct, the result need not be a literal value: it might be a field or variable name, a compound expression, or be NULL. NULL is not a value in SQL, but a state indicating that the value of the element either is unknown or it does not exist.

When you use NULL in logical Boolean expressions, the result will depend on the type of the operation and on other participating values. When you compare a value to NULL , the result will be unknown.

NULL means NULL but, in Firebird, the logical result unknown is also represented by NULL. It has already been shown that NOT NULL results in NULL. The interaction is a bit more complicated for the logical AND and logical OR operators:.

Up to and including Firebird 2. However, there are logical expressions predicates that can return true, false or unknown. A subquery is a special form of expression that is actually a query embedded within another query. Subqueries are written in the same way as regular SELECT queries, but they must be enclosed in parentheses.

Subquery expressions can be used in the following ways:. To obtain values or conditions for search predicates the WHERE , HAVING clauses. To produce a set that the enclosing query can select from, as though were a regular table or view. Subqueries like this appear in the FROM clause derived tables or in a Common Table Expression CTE.

A subquery can be correlated. A query is correlated when the subquery and the main query are interdependent. To process each record in the subquery, it is necessary to fetch a record in the main query; i. When subqueries are used to get the values of the output column in the SELECT list, a subquery must return a scalar result.

Subqueries used in search predicates, other than existential and quantified predicates, must return a scalar result; that is, not more than one column from not more than one matching row or aggregation.

Although it is reporting a genuine error, the message can be slightly misleading. If P resolves as TRUE, it succeeds. If it resolves to FALSE or NULL UNKNOWN , it fails.

A trap lies here, though: suppose the predicate, P , returns FALSE. In this case NOT P will return TRUE. On the other hand, if P returns NULL unknown , then NOT P returns NULL as well.

In SQL, predicates can appear in CHECK constraints, WHERE and HAVING clauses, CASE expressions, the IIF function and in the ON condition of JOIN clauses. An assertion is a statement about the data that, like a predicate, can resolve to TRUE, FALSE or NULL. Assertions consist of one or more predicates, possibly negated using NOT and connected by AND and OR operators.

Parentheses may be used for grouping predicates and controlling evaluation order. A predicate may embed other predicates. Evaluation sequence is in the outward direction, i. A comparison predicate consists of two expressions connected with a comparison operator. There are six traditional comparison operators:. For the complete list of comparison operators with their variant forms, see Comparison Operators. If one of the sides left or right of a comparison predicate has NULL in it, the value of the predicate will be UNKNOWN.

The following query will return no data, even if there are printers with no type specified for them, because a predicate that compares NULL with NULL returns NULL :. On the other hand, ptrtype can be tested for NULL and return a result: it is just that it is not a comparison test:.

When CHAR and VARCHAR fields are compared for equality, trailing spaces are ignored in all cases. The BETWEEN predicate tests whether a value falls within a specified range of two values.

NOT BETWEEN tests whether the value does not fall within that range. The operands for BETWEEN predicate are two arguments of compatible data types. The search is inclusive the values represented by both arguments are included in the search.

In other words, the BETWEEN predicate could be rewritten:. When BETWEEN is used in the search conditions of DML queries, the Firebird optimizer can use an index on the searched column, if it is available. The LIKE predicate compares the character-type expression with the pattern defined in the second expression. Case- or accent-sensitivity for the comparison is determined by the collation that is in use. A collation can be specified for either operand, if required. If the tested value matches the pattern, taking into account wildcard symbols, the predicate is TRUE.

If the search string contains either of the wildcard symbols, the ESCAPE clause can be used to specify an escape character.

Actually, the LIKE predicate does not use an index. So, if you need to search for the beginning of a string, it is recommended to use the STARTING WITH predicate instead of the LIKE predicate. Search for tables containing the underscore character in their names. The STARTING WITH predicate searches for a string or a string-like type that starts with the characters in its value argument. The search is case-sensitive. When STARTING WITH is used in the search conditions of DML queries, the Firebird optimizer can use an index on the searched column, if it exists.

It can be used for an alphanumeric string-like search on numbers and dates. However, if an accent-sensitive collation is in use then the search will be accent-sensitive. Search for changes in salaries with the date containing number 84 in this case, it means changes that took place in :. SIMILAR TO matches a string against an SQL regular expression pattern. If any operand is NULL , the result is NULL. Otherwise, the result is TRUE or FALSE. The following syntax defines the SQL regular expression format.

It is a complete and correct top-down definition. Feel free to skip it and read the next section, Building Regular Expressions , which uses a bottom-up approach, aimed at the rest of us. Within regular expressions, most characters represent themselves. The only exceptions are the special characters below:. A regular expression that contains no special or escape characters matches only strings that are identical to itself subject to the collation in use.

A bunch of characters enclosed in brackets define a character class. A character in the string matches a class in the pattern if the character is a member of the class:. Within a class definition, two characters connected by a hyphen define a range.

A range comprises the two endpoints and all the characters that lie between them in the active collation. Ranges can be placed anywhere in the class definition without special delimiters to keep them apart from the other elements. Latin letters a.. z and A.. With an accent-insensitive collation, this class also matches accented forms of these characters. Uppercase Latin letters A..

Also matches lowercase with case-insensitive collation and accented forms with accent-insensitive collation. Lowercase Latin letters a.. Also matches uppercase with case-insensitive collation and accented forms with accent-insensitive collation. Matches horizontal tab ASCII 9 , linefeed ASCII 10 , vertical tab ASCII 11 , formfeed ASCII 12 , carriage return ASCII 13 and space ASCII Including a predefined class has the same effect as including all its members.

Predefined classes are only allowed within class definitions. If you need to match against a predefined class and nothing more, place an extra pair of brackets around it. If a class definition starts with a caret, everything that follows is excluded from the class.

All other characters match:. If the caret is not placed at the start of the sequence, the class contains everything before the caret, except for the elements that also occur after the caret:.

If the braces contain two numbers separated by a comma, the second number not smaller than the first, then the item must be repeated at least the first number and at most the second number of times in order to match:. A match is made when the argument string matches at least one of the terms:. A subexpression is a regular expression in its own right.

It can contain all the elements allowed in a regular expression, and can also have quantifiers added to it. In order to match against a character that is special in regular expressions, that character has to be escaped. There is no default escape character; rather, the user specifies one when needed:. Two operands are considered DISTINCT if they have a different value or if one of them is NULL and the other non-null. They are NOT DISTINCT if they have the same value or if both of them are NULL.

Since NULL is not a value, these operators are not comparison operators. The IS [NOT] NULL predicate tests the assertion that the expression on the left side has a value IS NOT NULL or has no value IS NULL. In Firebird 3. This group of predicates includes those that use subqueries to submit values for all kinds of assertions in search conditions.

Existential predicates are so called because they use various methods to test for the existence or non-existence of some assertion, returning TRUE if the existence or non-existence is confirmed or FALSE otherwise. The EXISTS predicate uses a subquery expression as its argument. It returns TRUE if the subquery result would contain at least one row; otherwise it returns FALSE.

NOT EXISTS returns FALSE if the subquery result would contain at least one row; it returns TRUE otherwise. The IN predicate tests whether the value of the expression on the left side is present in the set of values specified on the right side. The set of values cannot have more than items.

The IN predicate can be replaced with the following equivalent forms:. When the IN predicate is used in the search conditions of DML queries, the Firebird optimizer can use an index on the searched column, if a suitable one exists. Queries specified using the IN predicate with a subquery can be replaced with a similar query using the EXISTS predicate.

For instance, the following query:. However, a query using NOT IN with a subquery does not always give the same result as its NOT EXISTS counterpart. The reason is that EXISTS always returns TRUE or FALSE, whereas IN returns NULL in one of these two cases:. when the test value has no match in the IN list and at least one list element is NULL. It is in only these two cases that IN will return NULL while the corresponding EXISTS predicate will return FALSE 'no matching row found'.

But, for the same data, NOT IN will return NULL , while NOT EXISTS will return TRUE , leading to opposite results.

Now, assume that the NY celebrities list is not empty and contains at least one NULL birthday. Then for every citizen who does not share his birthday with a NY celebrity, NOT IN will return NULL , because that is what IN does. The search condition is thereby not satisfied and the citizen will be left out of the SELECT result, which is wrong.

non-matches will have a NOT EXISTS result of TRUE and their records will be in the result set. If there is any chance of NULL s being encountered when searching for a non-match, you will want to use NOT EXISTS. The SINGULAR predicate takes a subquery as its argument and evaluates it as TRUE if the subquery returns exactly one result row; otherwise the predicate is evaluated as FALSE.

The subquery may list several output columns since the rows are not returned anyway. They are only tested for singular existence. The SINGULAR predicate can return only two values: TRUE or FALSE. A quantifier is a logical operator that sets the number of objects for which this assertion is true. It is not a numeric quantity, but a logical one that connects the assertion with the full set of possible objects. Such predicates are based on logical universal and existential quantifiers that are recognised in formal logic.

In subquery expressions, quantified predicates make it possible to compare separate values with the results of subqueries; they have the following common form:. When the ALL quantifier is used, the predicate is TRUE if every value returned by the subquery satisfies the condition in the predicate of the main query.

If the subquery returns an empty set, the predicate is TRUE for every left-side value, regardless of the operator. This may appear to be contradictory, because every left-side value will thus be considered both smaller and greater than, both equal to and unequal to, every element of the right-side stream. Nevertheless, it aligns perfectly with formal logic: if the set is empty, the predicate is true 0 times, i.

The quantifiers ANY and SOME are identical in their behaviour. Apparently, both are present in the SQL standard so that they could be used interchangeably in order to improve the readability of operators. When the ANY or the SOME quantifier is used, the predicate is TRUE if any of the values returned by the subquery satisfies the condition in the predicate of the main query. If the subquery would return no rows at all, the predicate is automatically considered as FALSE. DDL statements are used to create, modify and delete database objects that have been created by users.

When a DDL statement is committed, the metadata for the object are created, changed or deleted. This section describes how to create a database, connect to an existing database, alter the file structure of a database and how to delete one.

Optionally includes a port number or service name. Full path and file name including its extension. The file name must be specified according to the rules of the platform file system being used. Database alias previously created in the aliases. conf file. User name of the owner of the new database. It may consist of up to 31 characters. Password of the user name as the database owner.

The maximum length is 31 characters; however only the first 8 characters are considered. Page size for the database, in bytes. Possible values are the default , and Specifies the character set of the connection available to a client connecting after the database is successfully created.

Single quotes are required. The CREATE DATABASE statement creates a new database. You can use CREATE DATABASE or CREATE SCHEMA. They are synonymous. A database may consist of one or several files. The first main file is called the primary file , subsequent files are called secondary file[s]. Nowadays, multi-file databases are considered an anachronism. It made sense to use multi-file databases on old file systems where the size of any file is limited.

For instance, you could not create a file larger than 4 GB on FAT The primary file specification is the name of the database file and its extension with the full path to it according to the rules of the OS platform file system being used. The database file must not exist at the moment when the database is being created. If it does exist, you will get an error message and the database will not be created. If the full path to the database is not specified, the database will be created in one of the system directories.

The particular directory depends on the operating system. For this reason, unless you have a strong reason to prefer that situation, always specify the absolute path, when creating either the database or an alias for it. You can use aliases instead of the full path to the primary database file. If you create a database on a remote server, you should specify the remote server specification.

The remote server specification depends on the protocol being used. If you use the Named Pipes protocol to create a database on a Windows server, the primary file specification should look like this:.

Clauses for specifying the user name and the password, respectively, of an existing user in the security database security2. The user specified in the process of creating the database will be its owner. This will be important when considering database and object privileges. Clause for specifying the database page size. This size will be set for the primary file and all secondary files of the database.

If you specify the database page size less than 4,, it will be changed automatically to the default page size, 4, Other values not equal to either 4,, 8, or 16, will be changed to the closest smaller supported value. If the database page size is not specified, it is set to the default value of 4, Clause specifying the maximum size of the primary or secondary database file, in pages. When a database is created, its primary and secondary files will occupy the minimum number of pages necessary to store the system data, regardless of the value specified in the LENGTH clause.

The LENGTH value does not affect the size of the only or last, in a multi-file database file. The file will keep increasing its size automatically when necessary. Clause specifying the character set of the connection available after the database is successfully created. The character set NONE is used by default. Notice that the character set should be enclosed in a pair of apostrophes single quotes. Clause specifying the default character set for creating data structures of string data types.

Character sets are applied to CHAR , VARCHAR and BLOB TEXT data types. It is also possible to specify the default COLLATION for the default character set, making that collation sequence the default for the default character set. The default will be used for the entire database except where an alternative character set, with or without a specified collation, is used explicitly for a field, domain, variable, cast expression, etc. Clause that specifies the database page number at which the next secondary database file should start.

When the previous file is completely filled with data according to the specified page number, the system will start adding new data to the next database file. For the detailed description of this clause, see ALTER DATABASE. Databases are created in Dialect 3 by default. For the database to be created in SQL dialect 1, you will need to execute the statement SET SQL DIALECT 1 from script or the client application, e. in isql , before the CREATE DATABASE statement. Creating a database in Windows, located on disk D with a page size of 8, The owner of the database will be the user wizard.

The database will be in Dialect 1 and it will use WIN as its default character set. Creating a database in the Linux operating system with a page size of 4, The database will be in Dialect 3 and will use UTF8 as its default character set. Creating a database in Dialect 3 with UTF8 as its default character set. The primary file will contain up to 10, pages with a page size of 8, As soon as the primary file has reached the maximum number of pages, Firebird will start allocating pages to the secondary file test.

If that file is filled up to its maximum as well, test. fdb3 becomes the recipient of all new page allocations. As the last file, it has no page limit imposed on it by Firebird. New allocations will continue for as long as the file system allows it or until the storage device runs out of free space.

If a LENGTH parameter were supplied for this last file, it would be ignored. As far as file size and the use of secondary files are concerned, this database will behave exactly like the one in the previous example.

ALTER DATABASE , DROP DATABASE. Multiple ADD FILE clauses are allowed; and an ADD FILE clause that adds multiple files as in the example above can be mixed with others that add only one file.

The statement was documented incorrectly in the old InterBase 6 Language Reference. Only administrators have the authority to use ALTER DATABASE. Adds a secondary file to the database. It is necessary to specify the full path to the file and the name of the secondary file. The description for the secondary file is similar to the one given for the CREATE DATABASE statement. This clause does not actually add any file.

It just overrides the default name and path of the. delta file. To change the existing settings, you should delete the previously specified description of the. If the path and name of the. delta file are not overridden, the file will have the same path and name as the database, but with the. delta file extension. If only a file name is specified, the. delta file will be created in the current directory of the server. This is the clause that deletes the description path and name of the.

The file is not actually deleted. delta file from the database header. the same path and name as those of the database, but with the. delta extension. ALTER DATABASE with this clause freezes the main database file, making it possible to back it up safely using file system tools, even if users are connected and performing operations with data. Until the backup state of the database is reverted to NORMAL , all changes made to the database will be written to the.

delta difference file. Despite its syntax, a statement with the BEGIN BACKUP clause does not start a backup process but just creates the conditions for doing a task that requires the database file to be read-only temporarily.

A statement with this clause merges the. delta file with the main database file and restores the normal operation of the database. Once the END BACKUP process starts, the conditions no longer exist for creating safe backups by means of file system tools. Use of BEGIN BACKUP and END BACKUP and copying the database files with filesystem tools, is not safe with multi-file databases! Use this method only on single-file databases. Making a safe backup with the gbak utility remains possible at all times, although it is not recommended to run gbak while the database is in LOCKED or MERGE state.

Adding a secondary file to the database. As soon as pages are filled in the previous primary or secondary file, the Firebird engine will start adding data to the secondary file test4. CREATE DATABASE , DROP DATABASE. The DROP DATABASE statement deletes the current database. Before deleting a database, you have to connect to it. The statement deletes the primary file, all secondary files and all shadow files.

Only administrators have the authority to use DROP DATABASE. CREATE DATABASE , ALTER DATABASE. A shadow is an exact, page-by-page copy of a database. Once a shadow is created, all changes made in the database are immediately reflected in the shadow. If the primary database file becomes unavailable for some reason, the DBMS will switch to the shadow. The name of the shadow file and the path to it, in accord with the rules of the operating system. The CREATE SHADOW statement creates a new shadow.

The shadow starts duplicating the database right at the moment it is created. It is not possible for a user to connect to a shadow. Like a database, a shadow may be multi-file. The page size for shadow files is set to be equal to the database page size and cannot be changed. If a calamity occurs involving the original database, the system converts the shadow to a copy of the database and switches to it.

The shadow is then unavailable. What happens next depends on the MODE option. When a shadow is converted to a database, it becomes unavailable. A shadow might alternatively become unavailable because someone accidentally deletes its file, or the disk space where the shadow files are stored is exhausted or is itself damaged. Today, in a rare moment of bipartisan agreement, about four in ten Democrats, Republicans, and independents are optimistic that Americans of different political views will be able to come together.

Notably, in , half or more across parties, regions, and demographic groups were optimistic. Today, about eight in ten Democrats—compared to about half of independents and about one in ten Republicans—approve of Governor Newsom. Across demographic groups, about half or more approve of how Governor Newsom is handling his job. Approval of Congress among adults has been below 40 percent for all of after seeing a brief run above 40 percent for all of Democrats are far more likely than Republicans to approve of Congress.

Fewer than half across regions and demographic groups approve of Congress. Approval in March was at 44 percent for adults and 39 percent for likely voters. Across demographic groups, about half or more approve among women, younger adults, African Americans, Asian Americans, and Latinos. Views are similar across education and income groups, with just fewer than half approving.

Approval in March was at 41 percent for adults and 36 percent for likely voters. Across regions, approval reaches a majority only in the San Francisco Bay Area. Across demographic groups, approval reaches a majority only among African Americans. This map highlights the five geographic regions for which we present results; these regions account for approximately 90 percent of the state population. Residents of other geographic areas in gray are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately.

The PPIC Statewide Survey is directed by Mark Baldassare, president and CEO and survey director at the Public Policy Institute of California. Coauthors of this report include survey analyst Deja Thomas, who was the project manager for this survey; associate survey director and research fellow Dean Bonner; and survey analyst Rachel Lawler. The Californians and Their Government survey is supported with funding from the Arjay and Frances F.

Findings in this report are based on a survey of 1, California adult residents, including 1, interviewed on cell phones and interviewed on landline telephones. The sample included respondents reached by calling back respondents who had previously completed an interview in PPIC Statewide Surveys in the last six months. Interviews took an average of 19 minutes to complete. Interviewing took place on weekend days and weekday nights from October 14—23, Cell phone interviews were conducted using a computer-generated random sample of cell phone numbers.

Additionally, we utilized a registration-based sample RBS of cell phone numbers for adults who are registered to vote in California. All cell phone numbers with California area codes were eligible for selection. After a cell phone user was reached, the interviewer verified that this person was age 18 or older, a resident of California, and in a safe place to continue the survey e.

Cell phone respondents were offered a small reimbursement to help defray the cost of the call. Cell phone interviews were conducted with adults who have cell phone service only and with those who have both cell phone and landline service in the household. Landline interviews were conducted using a computer-generated random sample of telephone numbers that ensured that both listed and unlisted numbers were called.

Additionally, we utilized a registration-based sample RBS of landline phone numbers for adults who are registered to vote in California. All landline telephone exchanges in California were eligible for selection. For both cell phones and landlines, telephone numbers were called as many as eight times.

When no contact with an individual was made, calls to a number were limited to six. Also, to increase our ability to interview Asian American adults, we made up to three additional calls to phone numbers estimated by Survey Sampling International as likely to be associated with Asian American individuals. Accent on Languages, Inc. The survey sample was closely comparable to the ACS figures. To estimate landline and cell phone service in California, Abt Associates used state-level estimates released by the National Center for Health Statistics—which used data from the National Health Interview Survey NHIS and the ACS.

The estimates for California were then compared against landline and cell phone service reported in this survey. We also used voter registration data from the California Secretary of State to compare the party registration of registered voters in our sample to party registration statewide. The sampling error, taking design effects from weighting into consideration, is ±3. This means that 95 times out of , the results will be within 3.

The sampling error for unweighted subgroups is larger: for the 1, registered voters, the sampling error is ±4. For the sampling errors of additional subgroups, please see the table at the end of this section. Sampling error is only one type of error to which surveys are subject. Results may also be affected by factors such as question wording, question order, and survey timing. We present results for five geographic regions, accounting for approximately 90 percent of the state population.

Residents of other geographic areas are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately.

We also present results for congressional districts currently held by Democrats or Republicans, based on residential zip code and party of the local US House member.

We compare the opinions of those who report they are registered Democrats, registered Republicans, and no party preference or decline-to-state or independent voters; the results for those who say they are registered to vote in other parties are not large enough for separate analysis. We also analyze the responses of likely voters—so designated per their responses to survey questions about voter registration, previous election participation, intentions to vote this year, attention to election news, and current interest in politics.

The percentages presented in the report tables and in the questionnaire may not add to due to rounding. Additional details about our methodology can be found at www. pdf and are available upon request through surveys ppic. October 14—23, 1, California adult residents; 1, California likely voters English, Spanish. Margin of error ±3. Percentages may not add up to due to rounding. Overall, do you approve or disapprove of the way that Gavin Newsom is handling his job as governor of California?

Overall, do you approve or disapprove of the way that the California Legislature is handling its job? Do you think things in California are generally going in the right direction or the wrong direction? Thinking about your own personal finances—would you say that you and your family are financially better off, worse off, or just about the same as a year ago? Next, some people are registered to vote and others are not. Are you absolutely certain that you are registered to vote in California?

Are you registered as a Democrat, a Republican, another party, or are you registered as a decline-to-state or independent voter? Would you call yourself a strong Republican or not a very strong Republican? Do you think of yourself as closer to the Republican Party or Democratic Party? Which one of the seven state propositions on the November 8 ballot are you most interested in? Initiative Constitutional Amendment and Statute. It allows in-person sports betting at racetracks and tribal casinos, and requires that racetracks and casinos that offer sports betting to make certain payments to the state—such as to support state regulatory costs.

The fiscal impact is increased state revenues, possibly reaching tens of millions of dollars annually. Some of these revenues would support increased state regulatory and enforcement costs that could reach the low tens of millions of dollars annually. If the election were held today, would you vote yes or no on Proposition 26? Initiative Constitutional Amendment. It allows Indian tribes and affiliated businesses to operate online and mobile sports wagering outside tribal lands. It directs revenues to regulatory costs, homelessness programs, and nonparticipating tribes.

Some revenues would support state regulatory costs, possibly reaching the mid-tens of millions of dollars annually. If the election were held today, would you vote yes or no on Proposition 27? Initiative Statute. It allocates tax revenues to zero-emission vehicle purchase incentives, vehicle charging stations, and wildfire prevention.

If the election were held today, would you vote yes or no on Proposition 30? Do you agree or disagree with these statements? Overall, do you approve or disapprove of the way that Joe Biden is handling his job as president? Overall, do you approve or disapprove of the way Alex Padilla is handling his job as US Senator? Overall, do you approve or disapprove of the way Dianne Feinstein is handling her job as US Senator?

Overall, do you approve or disapprove of the way the US Congress is handling its job? Do you think things in the United States are generally going in the right direction or the wrong direction? How satisfied are you with the way democracy is working in the United States? Are you very satisfied, somewhat satisfied, not too satisfied, or not at all satisfied?

These days, do you feel [rotate] [1] optimistic [or] [2] pessimistic that Americans of different political views can still come together and work out their differences? What is your opinion with regard to race relations in the United States today? Would you say things are [rotate 1 and 2] [1] better , [2] worse , or about the same than they were a year ago?

When it comes to racial discrimination, which do you think is the bigger problem for the country today—[rotate] [1] People seeing racial discrimination where it really does NOT exist [or] [2] People NOT seeing racial discrimination where it really DOES exist?

Next, Next, would you consider yourself to be politically: [read list, rotate order top to bottom]. Generally speaking, how much interest would you say you have in politics—a great deal, a fair amount, only a little, or none? Mark Baldassare is president and CEO of the Public Policy Institute of California, where he holds the Arjay and Frances Fearing Miller Chair in Public Policy. He is a leading expert on public opinion and survey methodology, and has directed the PPIC Statewide Survey since He is an authority on elections, voter behavior, and political and fiscal reform, and the author of ten books and numerous publications.

Before joining PPIC, he was a professor of urban and regional planning in the School of Social Ecology at the University of California, Irvine, where he held the Johnson Chair in Civic Governance. He has conducted surveys for the Los Angeles Times , the San Francisco Chronicle , and the California Business Roundtable.

He holds a PhD in sociology from the University of California, Berkeley. Dean Bonner is associate survey director and research fellow at PPIC, where he coauthors the PPIC Statewide Survey—a large-scale public opinion project designed to develop an in-depth profile of the social, economic, and political attitudes at work in California elections and policymaking.

He has expertise in public opinion and survey research, political attitudes and participation, and voting behavior. Before joining PPIC, he taught political science at Tulane University and was a research associate at the University of New Orleans Survey Research Center. He holds a PhD and MA in political science from the University of New Orleans. Rachel Lawler is a survey analyst at the Public Policy Institute of California, where she works with the statewide survey team.

In that role, she led and contributed to a variety of quantitative and qualitative studies for both government and corporate clients. She holds an MA in American politics and foreign policy from the University College Dublin and a BA in political science from Chapman University. Deja Thomas is a survey analyst at the Public Policy Institute of California, where she works with the statewide survey team.

Prior to joining PPIC, she was a research assistant with the social and demographic trends team at the Pew Research Center. In that role, she contributed to a variety of national quantitative and qualitative survey studies. She holds a BA in psychology from the University of Hawaiʻi at Mānoa. This survey was supported with funding from the Arjay and Frances F. Ruben Barrales Senior Vice President, External Relations Wells Fargo.

Mollyann Brodie Executive Vice President and Chief Operating Officer Henry J. Kaiser Family Foundation. Bruce E.

Please check back soon for future events, and sign up to receive invitations to our events and briefings. December 1, Speaker Series on California's Future — Virtual Event. November 30, Virtual Event. November 18, Annual Water Conference — In-Person and Online. We believe in the power of good information to build a brighter future for California.

Help support our mission. Mark Baldassare , Dean Bonner , Rachel Lawler , and Deja Thomas. Supported with funding from the Arjay and Frances F. Miller Foundation and the James Irvine Foundation. California voters have now received their mail ballots, and the November 8 general election has entered its final stage. Amid rising prices and economic uncertainty—as well as deep partisan divisions over social and political issues—Californians are processing a great deal of information to help them choose state constitutional officers and state legislators and to make policy decisions about state propositions.

The midterm election also features a closely divided Congress, with the likelihood that a few races in California may determine which party controls the US House. These are among the key findings of a statewide survey on state and national issues conducted from October 14 to 23 by the Public Policy Institute of California:.

Today, there is a wide partisan divide: seven in ten Democrats are optimistic about the direction of the state, while 91 percent of Republicans and 59 percent of independents are pessimistic. Californians are much more pessimistic about the direction of the country than they are about the direction of the state. Majorities across all demographic groups and partisan groups, as well as across regions, are pessimistic about the direction of the United States.

A wide partisan divide exists: most Democrats and independents say their financial situation is about the same as a year ago, while solid majorities of Republicans say they are worse off. Regionally, about half in the San Francisco Bay Area and Los Angeles say they are about the same, while half in the Central Valley say they are worse off; residents elsewhere are divided between being worse off and the same.

The shares saying they are worse off decline as educational attainment increases. Strong majorities across partisan groups feel negatively, but Republicans and independents are much more likely than Democrats to say the economy is in poor shape. Today, majorities across partisan, demographic, and regional groups say they are following news about the gubernatorial election either very or fairly closely. In the upcoming November 8 election, there will be seven state propositions for voters.

Due to time constraints, our survey only asked about three ballot measures: Propositions 26, 27, and For each, we read the proposition number, ballot, and ballot label. Two of the state ballot measures were also included in the September survey Propositions 27 and 30 , while Proposition 26 was not.

This measure would allow in-person sports betting at racetracks and tribal casinos, requiring that racetracks and casinos offering sports betting make certain payments to the state to support state regulatory costs.

It also allows roulette and dice games at tribal casinos and adds a new way to enforce certain state gambling laws. Fewer than half of likely voters say the outcome of each of these state propositions is very important to them.

Today, 21 percent of likely voters say the outcome of Prop 26 is very important, 31 percent say the outcome of Prop 27 is very important, and 42 percent say the outcome of Prop 30 is very important. Today, when it comes to the importance of the outcome of Prop 26, one in four or fewer across partisan groups say it is very important to them.

About one in three across partisan groups say the outcome of Prop 27 is very important to them. Fewer than half across partisan groups say the outcome of Prop 30 is very important to them. When asked how they would vote if the election for the US House of Representatives were held today, 56 percent of likely voters say they would vote for or lean toward the Democratic candidate, while 39 percent would vote for or lean toward the Republican candidate.

Democratic candidates are preferred by a point margin in Democratic-held districts, while Republican candidates are preferred by a point margin in Republican-held districts. Abortion is another prominent issue in this election. When asked about the importance of abortion rights, 61 percent of likely voters say the issue is very important in determining their vote for Congress and another 20 percent say it is somewhat important; just 17 percent say it is not too or not at all important.

With the controlling party in Congress hanging in the balance, 51 percent of likely voters say they are extremely or very enthusiastic about voting for Congress this year; another 29 percent are somewhat enthusiastic while 19 percent are either not too or not at all enthusiastic.

Today, Democrats and Republicans have about equal levels of enthusiasm, while independents are much less likely to be extremely or very enthusiastic. As Californians prepare to vote in the upcoming midterm election, fewer than half of adults and likely voters are satisfied with the way democracy is working in the United States—and few are very satisfied. Satisfaction was higher in our February survey when 53 percent of adults and 48 percent of likely voters were satisfied with democracy in America.

Today, half of Democrats and about four in ten independents are satisfied, compared to about one in five Republicans. Notably, four in ten Republicans are not at all satisfied. In addition to the lack of satisfaction with the way democracy is working, Californians are divided about whether Americans of different political positions can still come together and work out their differences.

Forty-nine percent are optimistic, while 46 percent are pessimistic. Today, in a rare moment of bipartisan agreement, about four in ten Democrats, Republicans, and independents are optimistic that Americans of different political views will be able to come together.

Notably, in , half or more across parties, regions, and demographic groups were optimistic. Today, about eight in ten Democrats—compared to about half of independents and about one in ten Republicans—approve of Governor Newsom. Across demographic groups, about half or more approve of how Governor Newsom is handling his job. Approval of Congress among adults has been below 40 percent for all of after seeing a brief run above 40 percent for all of Democrats are far more likely than Republicans to approve of Congress.

Fewer than half across regions and demographic groups approve of Congress. Approval in March was at 44 percent for adults and 39 percent for likely voters. Across demographic groups, about half or more approve among women, younger adults, African Americans, Asian Americans, and Latinos.

Views are similar across education and income groups, with just fewer than half approving. Approval in March was at 41 percent for adults and 36 percent for likely voters. Across regions, approval reaches a majority only in the San Francisco Bay Area. Across demographic groups, approval reaches a majority only among African Americans. This map highlights the five geographic regions for which we present results; these regions account for approximately 90 percent of the state population.

Residents of other geographic areas in gray are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately.

The PPIC Statewide Survey is directed by Mark Baldassare, president and CEO and survey director at the Public Policy Institute of California. Coauthors of this report include survey analyst Deja Thomas, who was the project manager for this survey; associate survey director and research fellow Dean Bonner; and survey analyst Rachel Lawler. The Californians and Their Government survey is supported with funding from the Arjay and Frances F. Findings in this report are based on a survey of 1, California adult residents, including 1, interviewed on cell phones and interviewed on landline telephones.

The sample included respondents reached by calling back respondents who had previously completed an interview in PPIC Statewide Surveys in the last six months. Interviews took an average of 19 minutes to complete. Interviewing took place on weekend days and weekday nights from October 14—23, Cell phone interviews were conducted using a computer-generated random sample of cell phone numbers. Additionally, we utilized a registration-based sample RBS of cell phone numbers for adults who are registered to vote in California.

All cell phone numbers with California area codes were eligible for selection. After a cell phone user was reached, the interviewer verified that this person was age 18 or older, a resident of California, and in a safe place to continue the survey e. Cell phone respondents were offered a small reimbursement to help defray the cost of the call.

Cell phone interviews were conducted with adults who have cell phone service only and with those who have both cell phone and landline service in the household. Landline interviews were conducted using a computer-generated random sample of telephone numbers that ensured that both listed and unlisted numbers were called.

Additionally, we utilized a registration-based sample RBS of landline phone numbers for adults who are registered to vote in California. All landline telephone exchanges in California were eligible for selection. For both cell phones and landlines, telephone numbers were called as many as eight times.

When no contact with an individual was made, calls to a number were limited to six. Also, to increase our ability to interview Asian American adults, we made up to three additional calls to phone numbers estimated by Survey Sampling International as likely to be associated with Asian American individuals. Accent on Languages, Inc. The survey sample was closely comparable to the ACS figures. To estimate landline and cell phone service in California, Abt Associates used state-level estimates released by the National Center for Health Statistics—which used data from the National Health Interview Survey NHIS and the ACS.

The estimates for California were then compared against landline and cell phone service reported in this survey. We also used voter registration data from the California Secretary of State to compare the party registration of registered voters in our sample to party registration statewide.

The sampling error, taking design effects from weighting into consideration, is ±3. This means that 95 times out of , the results will be within 3.

The sampling error for unweighted subgroups is larger: for the 1, registered voters, the sampling error is ±4. For the sampling errors of additional subgroups, please see the table at the end of this section.

Sampling error is only one type of error to which surveys are subject. Results may also be affected by factors such as question wording, question order, and survey timing. We present results for five geographic regions, accounting for approximately 90 percent of the state population.

Residents of other geographic areas are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately. We also present results for congressional districts currently held by Democrats or Republicans, based on residential zip code and party of the local US House member.

We compare the opinions of those who report they are registered Democrats, registered Republicans, and no party preference or decline-to-state or independent voters; the results for those who say they are registered to vote in other parties are not large enough for separate analysis. We also analyze the responses of likely voters—so designated per their responses to survey questions about voter registration, previous election participation, intentions to vote this year, attention to election news, and current interest in politics.

The percentages presented in the report tables and in the questionnaire may not add to due to rounding. Additional details about our methodology can be found at www. pdf and are available upon request through surveys ppic. October 14—23, 1, California adult residents; 1, California likely voters English, Spanish. Margin of error ±3.

The University of Hawaii began using radio to send digital information as early as , using ALOHAnet. Governmental and non-governmental organizations use text messaging for communication between colleagues. The DROP SHADOW statement deletes the specified shadow for the database one is connected to. The Keller-Segel equations are widely used for describing chemotaxis in biology. By efficiently embedding and connecting financial services like banking, payments, and lending to help small businesses, we can reinvent how SMBs get paid and enable greater access to the vital funds they need at critical points in their journey. The following syntax defines the SQL regular expression format. He holds a PhD and MA in political science from the University of New Orleans.

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