疏鬆資料行
疏鬆資料行為已最佳化儲存位置來保存 Null 值的一般資料行。 疏鬆資料行會減少 Null 值的空間需求，但要付出擷取非 Null 值的更多成本負擔。 當空間至少節省了百分之 20 到 40 時，請考慮使用疏鬆資料行。
當您連線到執行 SQL Server 2008 (10.0.x) 和更新版本的伺服器時，SQL Server JDBC Driver 3.0 支援疏鬆資料行。 您可以使用 SQLServerDatabaseMetaData.getColumns、SQLServerDatabaseMetaData.getFunctionColumns 或 SQLServerDatabaseMetaData.getProcedureColumns 來判斷哪一個資料行是疏鬆資料行以及哪一個資料行是資料行集資料行。
此範例的程式碼檔案名稱為 SparseColumns.java，並位於下列位置：
\<installation directory>\sqljdbc_<version>\<language>\samples\sparse
資料行集是計算的資料行，可使用不具型別的 XML 形式傳回所有疏鬆資料行。 當資料表中的資料行數目很大或超過 1024 個，或者在個別疏鬆資料行上操作很麻煩時，請考慮使用資料行集。 資料行集最多可以包含 30,000 個資料行。
範例
描述
此範例示範如何使用偵測資料行集。 它也會示範如何剖析資料行集的 XML 輸出以取得疏鬆資料行中的資料。
程式碼清單是 Java 原始程式碼。 在編譯應用程式之前，請先變更連接字串。
程式碼
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);
}
}