稀疏列
稀疏列是对 Null 值采用优化的存储方式的普通列。 稀疏列减少了 Null 值的空间需求，但代价是检索非 Null 值的开销增加。 当至少能够节省 20% 到 40% 的空间时，才应考虑使用稀疏列。
当连接到运行 SQL Server 2008 (10.0.x) 及更高版本的服务器时，SQL Server JDBC Driver 3.0 支持稀疏列。 可以使用 SQLServerDatabaseMetaData.getColumns、SQLServerDatabaseMetaData.getFunctionColumns 或 SQLServerDatabaseMetaData.getProcedureColumns 确定哪个列是稀疏列以及哪个列是列集列。
此示例的代码文件名为 SparseColumns.java，位于以下位置：
\<installation directory>\sqljdbc_<version>\<language>\samples\sparse
列集是返回非类型化 XML 形式的所有稀疏列的计算列。 当表中有很多列、列数大于 1024 或分别对这些稀疏列进行操作很烦琐时，可考虑使用列集。 列集最多可以包含 30,000 个列。
示例
说明
此示例说明如何检测列集。 它还显示如何分析列集的 XML 输出，以便从稀疏列获取数据。
所列的代码是 Java 源代码。 在编译应用程序之前，更改连接字符串。
代码
import java.io.StringReader;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.ResultSetMetaData;
import java.sql.SQLException;
import java.sql.Statement;
import javax.xml.parsers.DocumentBuilder;
import javax.xml.parsers.DocumentBuilderFactory;
import org.w3c.dom.Document;
import org.w3c.dom.Node;
import org.w3c.dom.NodeList;
import org.xml.sax.InputSource;
public class SparseColumns {
public static void main(String args[]) {
// Create a variable for the connection string.
String connectionUrl = "jdbc:sqlserver://<server>:<port>;encrypt=true;databaseName=AdventureWorks;user=<user>;password=<password>";
try (Connection con = DriverManager.getConnection(connectionUrl); Statement stmt = con.createStatement()) {
createColdCallingTable(stmt);
// Determine the column set column
String columnSetColName = null;
String strCmd = "SELECT name FROM sys.columns WHERE object_id=(SELECT OBJECT_ID('ColdCalling')) AND is_column_set = 1";
try (ResultSet rs = stmt.executeQuery(strCmd)) {
if (rs.next()) {
columnSetColName = rs.getString(1);
System.out.println(columnSetColName + " is the column set column!");
}
}
strCmd = "SELECT * FROM ColdCalling";
try (ResultSet rs = stmt.executeQuery(strCmd)) {
// Iterate through the result set
ResultSetMetaData rsmd = rs.getMetaData();
DocumentBuilderFactory dbf = DocumentBuilderFactory.newInstance();
DocumentBuilder db = dbf.newDocumentBuilder();
InputSource is = new InputSource();
while (rs.next()) {
// Iterate through the columns
for (int i = 1; i <= rsmd.getColumnCount(); ++i) {
String name = rsmd.getColumnName(i);
String value = rs.getString(i);
// If this is the column set column
if (name.equalsIgnoreCase(columnSetColName)) {
System.out.println(name);
// Instead of printing the raw XML, parse it
if (value != null) {
// Add artificial root node "sparse" to ensure XML is well formed
String xml = "<sparse>" + value + "</sparse>";
is.setCharacterStream(new StringReader(xml));
Document doc = db.parse(is);
// Extract the NodeList from the artificial root node that was added
NodeList list = doc.getChildNodes();
Node root = list.item(0); // This is the <sparse> node
NodeList sparseColumnList = root.getChildNodes(); // These are the xml column nodes
// Iterate through the XML document
for (int n = 0; n < sparseColumnList.getLength(); ++n) {
Node sparseColumnNode = sparseColumnList.item(n);
String columnName = sparseColumnNode.getNodeName();
// The column value is not in the sparseColumNode, it is the value of the
// first child of it
Node sparseColumnValueNode = sparseColumnNode.getFirstChild();
String columnValue = sparseColumnValueNode.getNodeValue();
System.out.println("\t" + columnName + "\t: " + columnValue);
}
}
} else { // Just print the name + value of non-sparse columns
System.out.println(name + "\t: " + value);
}
}
System.out.println();// New line between rows
}
}
} catch (Exception e) {
e.printStackTrace();
}
}
private static void createColdCallingTable(Statement stmt) throws SQLException {
stmt.execute("if exists (select * from sys.objects where name = 'ColdCalling')" + "drop table ColdCalling");
String sql = "CREATE TABLE ColdCalling ( ID int IDENTITY(1,1) PRIMARY KEY, [Date] date, [Time] time, PositiveFirstName nvarchar(50) SPARSE, PositiveLastName nvarchar(50) SPARSE, SpecialPurposeColumns XML COLUMN_SET FOR ALL_SPARSE_COLUMNS );";
stmt.execute(sql);
sql = "INSERT ColdCalling ([Date], [Time]) VALUES ('10-13-09','07:05:24') ";
stmt.execute(sql);
sql = "INSERT ColdCalling ([Date], [Time], PositiveFirstName, PositiveLastName) VALUES ('07-20-09','05:00:24', 'AA', 'B') ";
stmt.execute(sql);
sql = "INSERT ColdCalling ([Date], [Time], PositiveFirstName, PositiveLastName) VALUES ('07-20-09','05:15:00', 'CC', 'DD') ";
stmt.execute(sql);
}
}