The previous article in this series, Developing with Apache Derby -- Hitting the Trifecta: Database development with Apache Derby, Part 3: Running scripts and inserting data, ended by running a script that inserted ten rows and then displayed these rows for validation. That article didn't discuss how the rows were selected for display because it focused on inserting data into an Apache Derby database. The topic of this article is the selection and extraction of data from an Apache Derby database. But before you can perform a database query, you must create a database that contains several tables populated with relevant data.
Rather than assuming you have such a database or requesting that you complete the steps listed in the previous articles in this series, this article provides a SQL script file called derby5.build.sql bundled in a .zip file called derby5.zip (see the Download section later in this article). This SQL script file first creates a database and then creates two tables within their own schema, inserts ten rows into each of these tables, and displays the contents of both tables for validation. To run the commands in this script file you can use any of the three methods discussed in the previous article in this series or follow along with the commands shown in Listing 1.
Listing 1. Initializing your Derby workspace
rb$ mkdir derbyWork rb$ cd derbyWork/ rb$ unzip ../derby5.zip Archive: ../derby5.zip inflating: derby.build.sql rb$ ls derby.build.sql rb$ java org.apache.derby.tools.ij < ../derby.build.sql ij version 10.1 ij>ij> ERROR 42Y07: Schema 'BIGDOG' does not exist ij> ERROR 42Y07: Schema 'BIGDOG' does not exist ij> 0 rows inserted/updated/deleted ij> 0 rows inserted/updated/deleted ij> 10 rows inserted/updated/deleted ij> 10 rows inserted/updated/deleted ij> ITEMNUMBER |PRICE |STOCKDATE |DESCRIPTION ------------------------------------------------------------------------ 1 |19.95 |2006-03-31|Hooded sweatshirt 2 |99.99 |2006-03-29|Beach umbrella 3 |0.99 |2006-02-28| 4 |29.95 |2006-02-10|Male bathing suit, blue 5 |49.95 |2006-02-20|Female bathing suit, one piece, aqua 6 |9.95 |2006-01-15|Child sand toy set 7 |24.95 |2005-12-20|White beach towel 8 |32.95 |2005-12-22|Blue-striped beach towel 9 |12.95 |2006-03-12|Flip-flop 10 |34.95 |2006-01-24|Open-toed sandal 10 rows selected ij> ITEMNUMBER |VENDORNUMB&|VENDORNAME ------------------------------------------------------ 1 |1 |Luna Vista Limited 2 |1 |Luna Vista Limited 3 |1 |Luna Vista Limited 4 |2 |Mikal Arroyo Incorporated 5 |2 |Mikal Arroyo Incorporated 6 |1 |Luna Vista Limited 7 |1 |Luna Vista Limited 8 |1 |Luna Vista Limited 9 |3 |Quiet Beach Industries 10 |3 |Quiet Beach Industries 10 rows selected ij> rb$
The commands shown in Listing 1 create and change into a work directory, called derbyWork in this example, expand the .zip file that contains the SQL build commands needed for the rest of this article, and execute the SQL commands within the script file using the
Apache Derby interactive SQL tool. Although you don't have to perform all of these commands, you do need to process the derby.build.sql script file because it creates two tables and fills them with data.
In this example, you may get one of several errors. For example, you may get a
database exists error or, as shown in Listing 1, a
schema does not exist error. Both of these errors can be safely ignored. If you get a different error, or if you don't get the list of rows with the
10 rows selected message, something went wrong that must be addressed. For more information on possible problems, see the first article in this series, Developing with Apache Derby -- Hitting the Trifecta: Introduction to Apache Derby, or the Apache Derby Web site (see the Resources section at the end of this article for a link).
In the SQL programming language, the task of performing a query falls to the
To provide all the query functionality required by database applications, the
capabilities are extensive. The rest of this article covers the basics of the
which let you build powerful queries for your database-enabled applications. First, the following section introduces the formal syntax of
The SELECT statement syntax
Formally, the syntax for the
SELECT statement is simple, as shown in Listing 2. The basic format is
SELECT ... FROM ... WHERE; you select the columns of interest from rows in a table or tables where certain conditions are satisfied. Of course, things can become considerably more complex. This article covers the basic features of
SELECT and defers the more advanced issues to subsequent articles.
Listing 2. The formal syntax for the SELECT statement
SELECT [ DISTINCT | ALL ] SelectItem [ , SelectItem ]* FROM clause [ WHERE clause ] [ GROUP BY clause ] [ HAVING clause ]
From the syntax in Listing 2, you can see that a basic
SELECT statement requires only a
SELECT and a
FROM; you must specify what data to select and indicate the location of the data of interest. Everything else is optional (as indicated by the square brackets). The
ALL keywords are optional qualifiers to indicate that either rows with unique values or all rows should be selected, respectively. By default,
ALL is implicitly assumed, and you can use only one
SELECT statement can have multiple columns listed following the
SELECT keyword. Apache Derby currently limits you to 1,012 elements following the
SELECT keyword -- meaning this is one limit that you'll probably never need to worry about! Multiple elements (or, more generally, column names) are separated by commas. For example,
SELECT a, b, c selects the three columns a, b, and c. To select all columns from a table,
you can use the asterisk character (
*) as a shorthand for all columns.
An important point to remember is that the result of any
SELECT statement is an Apache Derby
table, and you can use it in many of the same ways you use a more permanent table.
FROM component of a
SELECT statement indicates from which table (or multiple tables) the data will be extracted. This section focuses on selecting data from a single table; the last section in this article covers table joins and selecting data from multiple tables. In this case, the fully qualified name of the table to query must follow the
The rest of the
SELECT statement is optional. Before you build your first query, however, you should know the order in which Apache Derby evaluates the
SELECT statement components. When Apache Derby processes a query, the order of evaluation is:
When you break down the process Apache Derby follows when processing a query, this order is intuitive. First you must locate the data to be analyzed, after which you filter out the rows of interest. The next steps are to group related rows and, finally, to select the actual columns of interest.
Select rows from a table
To demonstrate a
SELECT statement, you can extract all the columns from the
products table located in the
bigdog schema, as shown in Listing 3.
Listing 3. Using the SELECT statement to extract rows from an Apache Derby table
rb$ java org.apache.derby.tools.ij ij version 10.1 ij> connect 'jdbc:derby:test' ; ij> SELECT * FROM bigdog.products ; ITEMNUMBER |PRICE |STOCKDATE |DESCRIPTION ------------------------------------------------------------------------ 1 |19.95 |2006-03-31|Hooded sweatshirt 2 |99.99 |2006-03-29|Beach umbrella 3 |0.99 |2006-02-28| 4 |29.95 |2006-02-10|Male bathing suit, blue 5 |49.95 |2006-02-20|Female bathing suit, one piece, aqua 6 |9.95 |2006-01-15|Child sand toy set 7 |24.95 |2005-12-20|White beach towel 8 |32.95 |2005-12-22|Blue-striped beach towel 9 |12.95 |2006-03-12|Flip-flop 10 |34.95 |2006-01-24|Open-toed sandal 10 rows selected ij> SELECT * FROM products ; ERROR 42X05: Table 'PRODUCTS' does not exist. ij> SELECT price, itemNumber, description FROM bigdog.products ; PRICE |ITEMNUMBER |DESCRIPTION ------------------------------------------------------------------------ 19.95 |1 |Hooded sweatshirt 99.99 |2 |Beach umbrella 0.99 |3 | 29.95 |4 |Male bathing suit, blue 49.95 |5 |Female bathing suit, one piece, aqua 9.95 |6 |Child sand toy set 24.95 |7 |White beach towel 32.95 |8 |Blue-striped beach towel 12.95 |9 |Flip-flop 34.95 |10 |Open-toed sandal 10 rows selected ij>
Before you can query a database in Apache Derby, you must establish a database connection. This requires that you start the
ij tool and issue the appropriate
connect command. In this example, the first query uses the
* shorthand to select all columns from the
bigdog.products table. This is the exact statement used in the SQL script file you executed at the start of this article. In that case, the
SELECT statement verified that the tables were created and loaded properly. The second SQL statement tries to perform the exact same query but without specifying the fully qualified name for the
products table. Because Apache Derby can't locate the table, an error is issued.
The final SQL statement explicitly lists three columns --
description -- after the
SELECT keyword. This demonstrates that you can pull out only those columns of interest, and you can also extract them from the table in a different order than they exist within the database. Explicitly listing the columns is a best practice (see the sidebar for more details).
The WHERE clause
Up to this point, you have only selected columns for all rows in a single table. This can be expensive in terms of query performance, especially if you only want a subset of the rows from a large table. A more efficient technique is to filter database rows by placing conditions in the
WHERE clause, which is evaluated immediately after the tables are specified within the
FROM clause. The rest of this section discusses some of the basic features that are enabled by using the
WHERE clause, including the ability to select rows that satisfy Boolean conditions as well as join multiple tables to perform more complex queries.
The simplest and most common use of the
WHERE clause is to filter the rows from a table before selecting any columns, as demonstrated in Listing 4.
Listing 4. Filtering rows in a query using the WHERE clause
ij> SELECT p.itemNumber, p.price FROM bigdog.products AS p WHERE p.price > 30.00 ; ITEMNUMBER |PRICE -------------------- 2 |99.99 5 |49.95 8 |32.95 10 |34.95 4 rows selected ij> SELECT * FROM bigdog.products WHERE price > 30.00 AND stockDate < '2006-01-01' ; ITEMNUMBER |PRICE |STOCKDATE |DESCRIPTION ------------------------------------------------------------------------ 8 |32.95 |2005-12-22|Blue-striped beach towel 1 row selected ij>
The first query shown in this example selects the
bigdog.products table for all rows where the
price column has a
value greater than $30.00. The second query extends this same query to select only those columns whose
has a value more than $30.00 and whose
stockDate column has a value
less than January 1, 2006. These two query restrictions are combined in this query by using the
You can perform a number of different Boolean operations within a
clause. Table 1 lists and provides examples of the basic SQL Boolean operations that you can use
in a query.
Table 1. Basic SQL Boolean operators
|Test if any built-in type is equal to a specified value.|
|Test if any built-in type is less than a specified value.|
|Test if any built-in type is greater than a specified value.|
|Test if any built-in type is less than or equal to a specified value.|
|Test if any built-in type is greater than or equal to a specified value.|
|Test if any built-in type is not equal to a specified value.|
|Test if an expression or value is null.|
|Test if an expression or value is not null.|
|Test if two expressions are both true or evaluate as nonzero.|
|Test if one or both of two expressions are true or evaluate as nonzero.|
|Test if an expression is false or evaluates as zero.|
|Test if a value lies inclusively between two other values (example is equivalent to |
|Test if a character expression matches a pattern, with the percent character (|
The first query also introduces the
AS clause, which you can use to create a table synonym. In these examples, you define a synonym
p for the fully qualified table name
bigdog.products. By defining a synonym, you can refer to
table quantities by using a shorter notation. This may not seem important when only one table is being referenced in a query, but the next section shows how to join multiple tables together within a query; in that case, providing table synonyms is very useful. You can also use an
clause to name the selected columns in a query. Doing so lets you control how the results are displayed, which is also demonstrated in the next section.
The second major function performed by a
WHERE clause is to join multiple tables together into a single table that can be queried more easily. Joining multiple tables is a powerful technique, and it can be complex when you're dealing with several large tables. Tables can be joined either explicitly, by using the
JOIN keyword, or implicitly, by using a
You join two tables by using an inner join or an outer join. An inner join is essentially the intersection of two tables, where the tables are matched by comparing the values of a key column, such as
itemNumber. The resulting table is composed of only rows that were matched
between the two tables. An outer join is more like a union of two tables, where the tables are matched by comparing the values of a key column, but
nonmatching rows are still included in the resulting table and filled with
NULL values as appropriate. Writing SQL queries that use these more advanced table joins will be addressed in future articles.
In the current simple scheme, the process is simple; Listing 5 performs an implicit inner join of the
bigdog.products table and the
Listing 5. Querying two tables using a table join
ij> SELECT p.price, p.description AS "Item", v.vendorName AS "Vendor" FROM bigdog.products AS p, bigdog.vendors AS v WHERE p.itemNumber = v.itemNumber ; PRICE |Item |Vendor -------------------------------------------------------------------------------- 19.95 |Hooded sweatshirt |Luna Vista Limited 99.99 |Beach umbrella |Luna Vista Limited 0.99 | |Luna Vista Limited 29.95 |Male bathing suit, blue |Mikal Arroyo Incorporated 49.95 |Female bathing suit, one-piece, aqua |Mikal Arroyo Incorporated 9.95 |Child sand toy set |Luna Vista Limited 24.95 |White beach towel |Luna Vista Limited 32.95 |Blue-striped beach towel |Luna Vista Limited 12.95 |Flip-flop |Quiet Beach Industries 34.95 |Open-toed sandal |Quiet Beach Industries 10 rows selected ij>
This query may seem complex, due primarily to its length. But by breaking it down line by line you can easily follow what's happening. First, you select two columns from the
bigdog.products table and one column from the
bigdog.vendors table and use an
AS clause to name these columns for the display with the
ij tool. Because the query joins these two tables (by using an implicit inner join), you can select columns from both tables. In the
FROM clause, you list both tables and provide aliases for them to simplify the full SQL statement. In the
WHERE clause, you provide the logic for joining the two tables, by explicitly instructing the Derby database engine to only select rows from the two tables that have matching values in their respective
itemNumber columns. In processing this query, the Derby database engine first pulls all rows out of the first (left) table in the query --
bigdog.products in this example -- and finds the row with a matching value in the
itemNumber column in the second (right) table in the query -- in this case,
This article introduced the
SELECT statement and demonstrated how to use it properly with Apache Derby to select and extract data from a database. The full functionality of the
SELECT statement is complex, but the basic concepts let you perform sophisticated queries that can extract multiple columns from one or more tables joined using an implicit inner join. The next article will discuss some of the more advanced functionality provided by the
SELECT statement, which lets you compute quantities within a SQL statement, change data types, and order the resulting data.
|Derby SQL scripts for this article||derby.build.zip||1KB|
- Check out the other articles in this series:
- " Developing with Apache Derby -- Hitting the Trifecta: Introduction to Apache Derby" (developerWorks, February 2006) introduces the Apache Derby database and provides the foundation for many topics in this series.
Developing with Apache Derby -- Hitting the Trifecta: Database development with Apache Derby, Part 1: Start working with Derby today" (developerWorks, March 2006) introduces the
ijtool and demonstrates how to use it to connect to an Apache Derby database.
- "Developing with Apache Derby -- Hitting the Trifecta: Database development with Apache Derby, Part 2: Schemas" (developerWorks, April 2006) covers several database concepts, including schemas, tables, and column data tapes, and gives you a simple introduction to SQL.
- " Developing with Apache Derby -- Hitting the Trifecta: Database development with Apache Derby, Part 3: Running scripts and inserting data" (developerWorks, May 2006) introduces the concept of executing SQL scripts with Apache Derby and demonstrates how to insert data into tables in an Apache Derby database.
- Access the Apache Derby project online manuals for more detailed information on how to use the Apache Derby database.
- Read an Apache Derby project tutorial that details how to download and install Apache Derby.
- Check out the developerWorks Apache Derby project area for articles, tutorials, and other resources to help you get started with Derby today.
- Visit the developerWorks Open source zone for extensive how-to information, tools, and project updates to help you develop with open source technologies and use them with IBM's products.
- Browse all the Apache articles and free Apache tutorials available in the developerWorks Open source zone.
- Browse for books on these and other technical topics at the Safari bookstore.
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