背景
大家应该都用过数据库自带的内置函数PIVOT和UNPIVOT来进行行列的互相转化,但是当我们在做数据转储的时候,如果这个动作是集成在自动化服务当中,想用java代码直接实现从源数据读出数据,经过转储以后直接插入目标表中,能不能实现呢?今天我们就来尝试一下!
方案
源表:
a | b | qty_2022_04_26 | qty_2022_04_27 | qty_2022_04_28 |
---|
aa | bb | 11 | 22 | 33 |
目标表:
a | b | qty_date | qty |
---|
aa | bb | 2022_04_26 | 11 | aa | bb | 2022_04_27 | 22 | aa | bb | 2022_04_28 | 33 |
我们所要实现的就是把源表经过行转列处理后变成目标表的格式,话不多说,直接上才艺。
code
public void test(Connection conn, String table, String Condition) throws SQLException, ClassNotFoundException {
ResultSet input_rs;
Statement st = conn.createStatement();
if (ObjectUtils.isEmpty(Condition)) {
Condition = "1=1";
}
String sql = "SELECT * FROM tableName where " + Condition;
input_rs = st.executeQuery(sql);
saveTable(input_rs);
input_rs.close();
conn.close();
}
public void saveTable(ResultSet input_rs) throws SQLException, ClassNotFoundException {
ResultSetMetaData rsmdl = input_rs.getMetaData();
Connection con = JDBCUtil.getConnection();
con.setAutoCommit(false);
String insert = "insert into dbo.targetTable values(?,?,?,?,?,?,?,?,?) ";
PreparedStatement ps = con.prepareStatement(insert);
Map<Integer, String> qtyColumnMap = new HashMap<>();
ResultSetMetaData rsmd = input_rs.getMetaData();
for (int i = 1; i <= rsmd.getColumnCount(); i++) {
String columnName = rsmd.getColumnName(i);
if (columnName.startsWith("QTY_")) {
qtyColumnMap.put(i, columnName);
}
}
int count = rsmdl.getColumnCount();
int i = 0;
while (input_rs.next()) {
List<String> newColumn = new ArrayList<>();
for (int j = 1; j <= count; j++) {
if (Objects.nonNull(qtyColumnMap.get(j))) {
for (int k = 1; k <= newColumn.size(); k++) {
ps.setString(k, newColumn.get(k - 1));
}
ps.setString(newColumn.size() + 1, qtyColumnMap.get(j).substring("QTY_".length()));
ps.setFloat(newColumn.size() + 2, input_rs.getFloat(j));
ps.addBatch();
i++;
} else {
newColumn.add(input_rs.getString(j));
}
}
if (i >= 2000) {
ps.executeBatch();
con.commit();
ps.clearBatch();
i = 0;
}
}
ps.executeBatch();
con.commit();
ps.clearBatch();
JDBCUtil.close(ps, con);
}
结语
希望上面的方案可以为您带来帮助,共勉!!!
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