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使用sql查询excel内容

news 文章来源：https://blog.csdn.net/sdgfafg_25/article/details/145301878 2025/5/18 10:21:40

1. 简介

我们在前面的文章中提到了calcite支持csv和json文件的数据源适配, 其实就是将文件解析成表然后以文件夹为schema, 然后将生成的schema注册到RootSehema(RootSchema是所有数据源schema的parent，多个不同数据源schema可以挂在同一个RootSchema下)下, 最终使用calcite的特性进行sql的解析查询返回.

但其实我们的数据文件一般使用excel进行存储,流转, 但很可惜, calcite本身没有excel的适配器, 但其实我们可以模仿calcite-file, 自己搞一个calcite-file-excel, 也可以熟悉calcite的工作原理.

2. 实现思路

因为excel有sheet的概念, 所以可以将一个excel解析成schema, 每个sheet解析成table, 实现步骤如下:

实现SchemaFactory重写create方法: schema工厂用于创建schema
继承AbstractSchema: schema描述类用于解析excel, 创建table(解析sheet)
继承AbstractTable, ScannableTable: table描述类提供字段信息和数据内容等(解析sheet data)

3. Excel样例

excel有两个sheet页, 分别是user_info 和 role_info如下:

ok, 万事具备.

4. Maven

<dependency><groupId>org.apache.poi</groupId><artifactId>poi-ooxml</artifactId><version>5.2.3</version>
</dependency><dependency><groupId>org.apache.poi</groupId><artifactId>poi</artifactId><version>5.2.3</version>
</dependency><dependency><groupId>org.apache.calcite</groupId><artifactId>calcite-core</artifactId><version>1.37.0</version>
</dependency>

5. 核心代码

5.1 SchemaFactory

package com.ldx.calcite.excel;import com.google.common.collect.Lists;
import org.apache.calcite.schema.Schema;
import org.apache.calcite.schema.SchemaFactory;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.commons.lang3.StringUtils;import java.io.File;
import java.util.List;
import java.util.Map;/*** schema factory*/
public class ExcelSchemaFactory implements SchemaFactory {public final static ExcelSchemaFactory INSTANCE = new ExcelSchemaFactory();private ExcelSchemaFactory(){}@Overridepublic Schema create(SchemaPlus parentSchema, String name, Map<String, Object> operand) {final Object filePath = operand.get("filePath");if (ObjectUtils.isEmpty(filePath)) {throw new NullPointerException("can not find excel file");}return this.create(filePath.toString());}public Schema create(String excelFilePath) {if (StringUtils.isBlank(excelFilePath)) {throw new NullPointerException("can not find excel file");}return this.create(new File(excelFilePath));}public Schema create(File excelFile) {if (ObjectUtils.isEmpty(excelFile) || !excelFile.exists()) {throw new NullPointerException("can not find excel file");}if (!excelFile.isFile() || !isExcelFile(excelFile)) {throw new RuntimeException("can not find excel file: " + excelFile.getAbsolutePath());}return new ExcelSchema(excelFile);}protected List<String> supportedFileSuffix() {return Lists.newArrayList("xls", "xlsx");}private boolean isExcelFile(File excelFile) {if (ObjectUtils.isEmpty(excelFile)) {return false;}final String name = excelFile.getName();return StringUtils.endsWithAny(name, this.supportedFileSuffix().toArray(new String[0]));}
}

schema中有多个重载的create方法用于方便的创建schema, 最终将excel file 交给ExcelSchema创建一个schema对象

5.2 Schema

package com.ldx.calcite.excel;import org.apache.calcite.schema.Table;
import org.apache.calcite.schema.impl.AbstractSchema;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.poi.ss.usermodel.Sheet;
import org.apache.poi.ss.usermodel.Workbook;
import org.apache.poi.ss.usermodel.WorkbookFactory;
import org.testng.collections.Maps;import java.io.File;
import java.util.Iterator;
import java.util.Map;/*** schema*/
public class ExcelSchema extends AbstractSchema {private final File excelFile;private Map<String, Table> tableMap;public ExcelSchema(File excelFile) {this.excelFile = excelFile;}@Overrideprotected Map<String, Table> getTableMap() {if (ObjectUtils.isEmpty(tableMap)) {tableMap = createTableMap();}return tableMap;}private Map<String, Table> createTableMap() {final Map<String, Table> result = Maps.newHashMap();try (Workbook workbook = WorkbookFactory.create(excelFile)) {final Iterator<Sheet> sheetIterator = workbook.sheetIterator();while (sheetIterator.hasNext()) {final Sheet sheet = sheetIterator.next();final ExcelScannableTable excelScannableTable = new ExcelScannableTable(sheet, null);result.put(sheet.getSheetName(), excelScannableTable);}}catch (Exception ignored) {}return result;}
}

schema类读取Excel file, 并循环读取sheet, 将每个sheet解析成ExcelScannableTable并存储

5.3 Table

package com.ldx.calcite.excel;import com.google.common.collect.Lists;
import com.ldx.calcite.excel.enums.JavaFileTypeEnum;
import org.apache.calcite.DataContext;
import org.apache.calcite.adapter.java.JavaTypeFactory;
import org.apache.calcite.linq4j.Enumerable;
import org.apache.calcite.linq4j.Linq4j;
import org.apache.calcite.rel.type.RelDataType;
import org.apache.calcite.rel.type.RelDataTypeFactory;
import org.apache.calcite.rel.type.RelProtoDataType;
import org.apache.calcite.schema.ScannableTable;
import org.apache.calcite.schema.impl.AbstractTable;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.calcite.util.Pair;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.ss.usermodel.Row;
import org.apache.poi.ss.usermodel.Sheet;
import org.checkerframework.checker.nullness.qual.Nullable;import java.util.List;/*** table*/
public class ExcelScannableTable extends AbstractTable implements ScannableTable {private final RelProtoDataType protoRowType;private final Sheet sheet;private RelDataType rowType;private List<JavaFileTypeEnum> fieldTypes;private List<Object[]> rowDataList;public ExcelScannableTable(Sheet sheet, RelProtoDataType protoRowType) {this.protoRowType = protoRowType;this.sheet = sheet;}@Overridepublic Enumerable<@Nullable Object[]> scan(DataContext root) {JavaTypeFactory typeFactory = root.getTypeFactory();final List<JavaFileTypeEnum> fieldTypes = this.getFieldTypes(typeFactory);if (rowDataList == null) {rowDataList = readExcelData(sheet, fieldTypes);}return Linq4j.asEnumerable(rowDataList);}@Overridepublic RelDataType getRowType(RelDataTypeFactory typeFactory) {if (ObjectUtils.isNotEmpty(protoRowType)) {return protoRowType.apply(typeFactory);}if (ObjectUtils.isEmpty(rowType)) {rowType = deduceRowType((JavaTypeFactory) typeFactory, sheet, null);}return rowType;}public List<JavaFileTypeEnum> getFieldTypes(RelDataTypeFactory typeFactory) {if (fieldTypes == null) {fieldTypes = Lists.newArrayList();deduceRowType((JavaTypeFactory) typeFactory, sheet, fieldTypes);}return fieldTypes;}private List<Object[]> readExcelData(Sheet sheet, List<JavaFileTypeEnum> fieldTypes) {List<Object[]> rowDataList = Lists.newArrayList();for (int rowIndex = 1; rowIndex <= sheet.getLastRowNum(); rowIndex++) {Row row = sheet.getRow(rowIndex);Object[] rowData = new Object[fieldTypes.size()];for (int i = 0; i < row.getLastCellNum(); i++) {final JavaFileTypeEnum javaFileTypeEnum = fieldTypes.get(i);Cell cell = row.getCell(i, Row.MissingCellPolicy.CREATE_NULL_AS_BLANK);final Object cellValue = javaFileTypeEnum.getCellValue(cell);rowData[i] = cellValue;}rowDataList.add(rowData);}return rowDataList;}public static RelDataType deduceRowType(JavaTypeFactory typeFactory, Sheet sheet, List<JavaFileTypeEnum> fieldTypes) {final List<String> names = Lists.newArrayList();final List<RelDataType> types = Lists.newArrayList();if (sheet != null) {Row headerRow = sheet.getRow(0);if (headerRow != null) {for (int i = 0; i < headerRow.getLastCellNum(); i++) {Cell cell = headerRow.getCell(i, Row.MissingCellPolicy.CREATE_NULL_AS_BLANK);String[] columnInfo = cell.getStringCellValue().split(":");String columnName = columnInfo[0].trim();String columnType = null;if (columnInfo.length == 2) {columnType = columnInfo[1].trim();}final JavaFileTypeEnum javaFileType = JavaFileTypeEnum.of(columnType).orElse(JavaFileTypeEnum.UNKNOWN);final RelDataType sqlType = typeFactory.createSqlType(javaFileType.getSqlTypeName());names.add(columnName);types.add(sqlType);if (fieldTypes != null) {fieldTypes.add(javaFileType);}}}}if (names.isEmpty()) {names.add("line");types.add(typeFactory.createSqlType(SqlTypeName.VARCHAR));}return typeFactory.createStructType(Pair.zip(names, types));}
}

table类中其中有两个比较关键的方法

scan: 扫描表内容, 我们这里将sheet页面的数据内容解析存储最后交给calcite

getRowType: 获取字段信息, 我们这里默认使用第一条记录作为表头(row[0]) 并解析为字段信息, 字段规则跟csv一样 name:string, 冒号前面的是字段key, 冒号后面的是字段类型, 如果未指定字段类型, 则解析为UNKNOWN, 后续JavaFileTypeEnum会进行类型推断, 最终在结果处理时calcite也会进行推断

deduceRowType: 推断字段类型, 方法中使用JavaFileTypeEnum枚举类对java type & sql type & 字段值转化处理方法进行管理

5.4 ColumnTypeEnum

package com.ldx.calcite.excel.enums;import lombok.Getter;
import lombok.extern.slf4j.Slf4j;
import org.apache.calcite.avatica.util.DateTimeUtils;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.commons.lang3.time.FastDateFormat;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.ss.usermodel.DateUtil;
import org.apache.poi.ss.util.CellUtil;import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Arrays;
import java.util.Date;
import java.util.Optional;
import java.util.TimeZone;
import java.util.function.Function;/*** type converter*/
@Slf4j
@Getter
public enum JavaFileTypeEnum {STRING("string", SqlTypeName.VARCHAR, Cell::getStringCellValue),BOOLEAN("boolean", SqlTypeName.BOOLEAN, Cell::getBooleanCellValue),BYTE("byte", SqlTypeName.TINYINT, Cell::getStringCellValue),CHAR("char", SqlTypeName.CHAR, Cell::getStringCellValue),SHORT("short", SqlTypeName.SMALLINT, Cell::getNumericCellValue),INT("int", SqlTypeName.INTEGER, cell -> (Double.valueOf(cell.getNumericCellValue()).intValue())),LONG("long", SqlTypeName.BIGINT, cell -> (Double.valueOf(cell.getNumericCellValue()).longValue())),FLOAT("float", SqlTypeName.REAL, Cell::getNumericCellValue),DOUBLE("double", SqlTypeName.DOUBLE, Cell::getNumericCellValue),DATE("date", SqlTypeName.DATE, getValueWithDate()),TIMESTAMP("timestamp", SqlTypeName.TIMESTAMP, getValueWithTimestamp()),TIME("time", SqlTypeName.TIME, getValueWithTime()),UNKNOWN("unknown", SqlTypeName.UNKNOWN, getValueWithUnknown()),;// cell typeprivate final String typeName;// sql typeprivate final SqlTypeName sqlTypeName;// value convert funcprivate final Function<Cell, Object> cellValueFunc;private static final FastDateFormat TIME_FORMAT_DATE;private static final FastDateFormat TIME_FORMAT_TIME;private static final FastDateFormat TIME_FORMAT_TIMESTAMP;static {final TimeZone gmt = TimeZone.getTimeZone("GMT");TIME_FORMAT_DATE = FastDateFormat.getInstance("yyyy-MM-dd", gmt);TIME_FORMAT_TIME = FastDateFormat.getInstance("HH:mm:ss", gmt);TIME_FORMAT_TIMESTAMP = FastDateFormat.getInstance("yyyy-MM-dd HH:mm:ss", gmt);}JavaFileTypeEnum(String typeName, SqlTypeName sqlTypeName, Function<Cell, Object> cellValueFunc) {this.typeName = typeName;this.sqlTypeName = sqlTypeName;this.cellValueFunc = cellValueFunc;}public static Optional<JavaFileTypeEnum> of(String typeName) {return Arrays.stream(values()).filter(type -> StringUtils.equalsIgnoreCase(typeName, type.getTypeName())).findFirst();}public static SqlTypeName findSqlTypeName(String typeName) {final Optional<JavaFileTypeEnum> javaFileTypeOptional = of(typeName);if (javaFileTypeOptional.isPresent()) {return javaFileTypeOptional.get().getSqlTypeName();}return SqlTypeName.UNKNOWN;}public Object getCellValue(Cell cell) {return cellValueFunc.apply(cell);}public static Function<Cell, Object> getValueWithUnknown() {return cell -> {if (ObjectUtils.isEmpty(cell)) {return null;}switch (cell.getCellType()) {case STRING:return cell.getStringCellValue();case NUMERIC:if (DateUtil.isCellDateFormatted(cell)) {// 如果是日期类型，返回日期对象return cell.getDateCellValue();}else {// 否则返回数值return cell.getNumericCellValue();}case BOOLEAN:return cell.getBooleanCellValue();case FORMULA:// 对于公式单元格，先计算公式结果，再获取其值try {return cell.getNumericCellValue();}catch (Exception e) {try {return cell.getStringCellValue();}catch (Exception ex) {log.error("parse unknown data error, cellRowIndex:{}, cellColumnIndex:{}", cell.getRowIndex(), cell.getColumnIndex(), e);return null;}}case BLANK:return "";default:return null;}};}public static Function<Cell, Object> getValueWithDate() {return cell -> {Date date = cell.getDateCellValue();if(ObjectUtils.isEmpty(date)) {return null;}try {final String formated = new SimpleDateFormat("yyyy-MM-dd").format(date);Date newDate = TIME_FORMAT_DATE.parse(formated);return (int) (newDate.getTime() / DateTimeUtils.MILLIS_PER_DAY);}catch (ParseException e) {log.error("parse date error, date:{}", date, e);}return null;};}public static Function<Cell, Object> getValueWithTimestamp() {return cell -> {Date date = cell.getDateCellValue();if(ObjectUtils.isEmpty(date)) {return null;}try {final String formated = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(date);Date newDate = TIME_FORMAT_TIMESTAMP.parse(formated);return (int) newDate.getTime();}catch (ParseException e) {log.error("parse timestamp error, date:{}", date, e);}return null;};}public static Function<Cell, Object> getValueWithTime() {return cell -> {Date date = cell.getDateCellValue();if(ObjectUtils.isEmpty(date)) {return null;}try {final String formated = new SimpleDateFormat("HH:mm:ss").format(date);Date newDate = TIME_FORMAT_TIME.parse(formated);return newDate.getTime();}catch (ParseException e) {log.error("parse time error, date:{}", date, e);}return null;};}
}

该枚举类主要管理了java type& sql type & cell value convert func, 方便统一管理类型映射及单元格内容提取时的转换方法(这里借用了java8 function函数特性)

注: 这里的日期转换只能这样写, 即使用GMT的时区(抄的calcite-file), 要不然输出的日期时间一直有时差...

6. 测试查询

package com.ldx.calcite;import com.ldx.calcite.excel.ExcelSchemaFactory;
import lombok.SneakyThrows;
import lombok.extern.slf4j.Slf4j;
import org.apache.calcite.config.CalciteConnectionProperty;
import org.apache.calcite.jdbc.CalciteConnection;
import org.apache.calcite.schema.Schema;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.calcite.util.Sources;
import org.junit.jupiter.api.AfterAll;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.testng.collections.Maps;import java.net.URL;
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 java.util.Map;
import java.util.Properties;@Slf4j
public class CalciteExcelTest {private static Connection connection;private static SchemaPlus rootSchema;private static CalciteConnection calciteConnection;@BeforeAll@SneakyThrowspublic static void beforeAll() {Properties info = new Properties();// 不区分sql大小写info.setProperty(CalciteConnectionProperty.CASE_SENSITIVE.camelName(), "false");// 创建Calcite连接connection = DriverManager.getConnection("jdbc:calcite:", info);calciteConnection = connection.unwrap(CalciteConnection.class);// 构建RootSchema，在Calcite中，RootSchema是所有数据源schema的parent，多个不同数据源schema可以挂在同一个RootSchema下rootSchema = calciteConnection.getRootSchema();}@Test@SneakyThrowspublic void test_execute_query() {final Schema schema = ExcelSchemaFactory.INSTANCE.create(resourcePath("file/test.xlsx"));rootSchema.add("test", schema);// 设置默认的schemacalciteConnection.setSchema("test");final Statement statement = calciteConnection.createStatement();ResultSet resultSet = statement.executeQuery("SELECT * FROM user_info");printResultSet(resultSet);System.out.println("=========");ResultSet resultSet2 = statement.executeQuery("SELECT * FROM test.user_info where id > 110 and birthday > '2003-01-01'");printResultSet(resultSet2);System.out.println("=========");ResultSet resultSet3 = statement.executeQuery("SELECT * FROM test.user_info ui inner join  test.role_info ri on ui.role_id = ri.id");printResultSet(resultSet3);}@AfterAll@SneakyThrowspublic static void closeResource() {connection.close();}private static String resourcePath(String path) {final URL url = CalciteExcelTest.class.getResource("/" + path);return Sources.of(url).file().getAbsolutePath();}public static void printResultSet(ResultSet resultSet) throws SQLException {// 获取 ResultSet 元数据ResultSetMetaData metaData = resultSet.getMetaData();// 获取列数int columnCount = metaData.getColumnCount();log.info("Number of columns: {}",columnCount);// 遍历 ResultSet 并打印结果while (resultSet.next()) {final Map<String, String> item = Maps.newHashMap();// 遍历每一列并打印for (int i = 1; i <= columnCount; i++) {String columnName = metaData.getColumnName(i);String columnValue = resultSet.getString(i);item.put(columnName, columnValue);}log.info(item.toString());}}
}

测试结果如下:

文章转载自：张铁牛

原文链接：4. 使用sql查询excel内容 - 张铁牛 - 博客园

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