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Microsoft JDBC Driver for SQL Server.
The Azure Key Vault feature in Microsoft JDBC Driver for SQL Server depends on
Azure SDK for JAVA and Azure Active Directory Library For Java.
/*
* Microsoft JDBC Driver for SQL Server
*
* Copyright(c) Microsoft Corporation All rights reserved.
*
* This program is made available under the terms of the MIT License. See the LICENSE file in the project root for more information.
*/
package com.microsoft.sqlserver.jdbc;
import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.UnsupportedEncodingException;
import java.math.BigDecimal;
import java.math.RoundingMode;
import java.sql.Types;
import java.text.DecimalFormat;
import java.text.MessageFormat;
import java.time.OffsetDateTime;
import java.time.OffsetTime;
import java.time.format.DateTimeFormatter;
import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
/**
* A simple implementation of the ISQLServerBulkRecord interface that can be used to read in the basic Java data types from a delimited file where
* each line represents a row of data.
*/
public class SQLServerBulkCSVFileRecord implements ISQLServerBulkRecord, java.lang.AutoCloseable {
/*
* Class to represent the column metadata
*/
private class ColumnMetadata {
String columnName;
int columnType;
int precision;
int scale;
DateTimeFormatter dateTimeFormatter = null;
ColumnMetadata(String name,
int type,
int precision,
int scale,
DateTimeFormatter dateTimeFormatter) {
columnName = name;
columnType = type;
this.precision = precision;
this.scale = scale;
this.dateTimeFormatter = dateTimeFormatter;
}
}
/*
* Resources associated with reading in the file
*/
private BufferedReader fileReader;
private InputStreamReader sr;
private FileInputStream fis;
/*
* Metadata to represent the columns in the file. Each column should be mapped to its corresponding position within the file (from position 1 and
* onwards)
*/
private Map columnMetadata;
/*
* Current line of data to parse.
*/
private String currentLine = null;
/*
* Delimiter to parse lines with.
*/
private final String delimiter;
/*
* Contains all the column names if firstLineIsColumnNames is true
*/
private String[] columnNames = null;
/*
* Contains the format that java.sql.Types.TIMESTAMP_WITH_TIMEZONE data should be read in as.
*/
private DateTimeFormatter dateTimeFormatter = null;
/*
* Contains the format that java.sql.Types.TIME_WITH_TIMEZONE data should be read in as.
*/
private DateTimeFormatter timeFormatter = null;
/*
* Class name for logging.
*/
private static final String loggerClassName = "com.microsoft.sqlserver.jdbc.SQLServerBulkCSVFileRecord";
/*
* Logger
*/
private static final java.util.logging.Logger loggerExternal = java.util.logging.Logger.getLogger(loggerClassName);
/**
* Creates a simple reader to parse data from a delimited file with the given encoding.
*
* @param fileToParse
* File to parse data from
* @param encoding
* Charset encoding to use for reading the file, or NULL for the default encoding.
* @param delimiter
* Delimiter to used to separate each column
* @param firstLineIsColumnNames
* True if the first line of the file should be parsed as column names; false otherwise
* @throws SQLServerException
* If the arguments are invalid, there are any errors in reading the file, or the file is empty
*/
public SQLServerBulkCSVFileRecord(String fileToParse,
String encoding,
String delimiter,
boolean firstLineIsColumnNames) throws SQLServerException {
loggerExternal.entering(loggerClassName, "SQLServerBulkCSVFileRecord",
new Object[] {fileToParse, encoding, delimiter, firstLineIsColumnNames});
if (null == fileToParse) {
throwInvalidArgument("fileToParse");
}
else if (null == delimiter) {
throwInvalidArgument("delimiter");
}
this.delimiter = delimiter;
try {
// Create the file reader
fis = new FileInputStream(fileToParse);
if (null == encoding || 0 == encoding.length()) {
sr = new InputStreamReader(fis);
}
else {
sr = new InputStreamReader(fis, encoding);
}
fileReader = new BufferedReader(sr);
if (firstLineIsColumnNames) {
currentLine = fileReader.readLine();
if (null != currentLine) {
columnNames = currentLine.split(delimiter, -1);
}
}
}
catch (UnsupportedEncodingException unsupportedEncoding) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_unsupportedEncoding"));
throw new SQLServerException(form.format(new Object[] {encoding}), null, 0, unsupportedEncoding);
}
catch (Exception e) {
throw new SQLServerException(null, e.getMessage(), null, 0, false);
}
columnMetadata = new HashMap<>();
loggerExternal.exiting(loggerClassName, "SQLServerBulkCSVFileRecord");
}
/**
* Creates a simple reader to parse data from a delimited file with the given encoding.
*
* @param fileToParse
* InputStream to parse data from
* @param encoding
* Charset encoding to use for reading the file, or NULL for the default encoding.
* @param delimiter
* Delimiter to used to separate each column
* @param firstLineIsColumnNames
* True if the first line of the file should be parsed as column names; false otherwise
* @throws SQLServerException
* If the arguments are invalid, there are any errors in reading the file, or the file is empty
*/
public SQLServerBulkCSVFileRecord(InputStream fileToParse,
String encoding,
String delimiter,
boolean firstLineIsColumnNames) throws SQLServerException {
loggerExternal.entering(loggerClassName, "SQLServerBulkCSVFileRecord",
new Object[] {fileToParse, encoding, delimiter, firstLineIsColumnNames});
if (null == fileToParse) {
throwInvalidArgument("fileToParse");
}
else if (null == delimiter) {
throwInvalidArgument("delimiter");
}
this.delimiter = delimiter;
try {
if (null == encoding || 0 == encoding.length()) {
sr = new InputStreamReader(fileToParse);
}
else {
sr = new InputStreamReader(fileToParse, encoding);
}
fileReader = new BufferedReader(sr);
if (firstLineIsColumnNames) {
currentLine = fileReader.readLine();
if (null != currentLine) {
columnNames = currentLine.split(delimiter, -1);
}
}
}
catch (UnsupportedEncodingException unsupportedEncoding) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_unsupportedEncoding"));
throw new SQLServerException(form.format(new Object[] {encoding}), null, 0, unsupportedEncoding);
}
catch (Exception e) {
throw new SQLServerException(null, e.getMessage(), null, 0, false);
}
columnMetadata = new HashMap<>();
loggerExternal.exiting(loggerClassName, "SQLServerBulkCSVFileRecord");
}
/**
* Creates a simple reader to parse data from a CSV file with the given encoding.
*
* @param fileToParse
* File to parse data from
* @param encoding
* Charset encoding to use for reading the file.
* @param firstLineIsColumnNames
* True if the first line of the file should be parsed as column names; false otherwise
* @throws SQLServerException
* If the arguments are invalid, there are any errors in reading the file, or the file is empty
*/
public SQLServerBulkCSVFileRecord(String fileToParse,
String encoding,
boolean firstLineIsColumnNames) throws SQLServerException {
this(fileToParse, encoding, ",", firstLineIsColumnNames);
}
/**
* Creates a simple reader to parse data from a CSV file with the default encoding.
*
* @param fileToParse
* File to parse data from
* @param firstLineIsColumnNames
* True if the first line of the file should be parsed as column names; false otherwise
* @throws SQLServerException
* If the arguments are invalid, there are any errors in reading the file, or the file is empty
*/
public SQLServerBulkCSVFileRecord(String fileToParse,
boolean firstLineIsColumnNames) throws SQLServerException {
this(fileToParse, null, ",", firstLineIsColumnNames);
}
/**
* Adds metadata for the given column in the file.
*
* @param positionInFile
* Indicates which column the metadata is for. Columns start at 1.
* @param name
* Name for the column (optional if only using column ordinal in a mapping for SQLServerBulkCopy operation)
* @param jdbcType
* JDBC data type of the column
* @param precision
* Precision for the column (ignored for the appropriate data types)
* @param scale
* Scale for the column (ignored for the appropriate data types)
* @param dateTimeFormatter
* format to parse data that is sent
* @throws SQLServerException
* when an error occurs
*/
public void addColumnMetadata(int positionInFile,
String name,
int jdbcType,
int precision,
int scale,
DateTimeFormatter dateTimeFormatter) throws SQLServerException {
addColumnMetadataInternal(positionInFile, name, jdbcType, precision, scale, dateTimeFormatter);
}
/**
* Adds metadata for the given column in the file.
*
* @param positionInFile
* Indicates which column the metadata is for. Columns start at 1.
* @param name
* Name for the column (optional if only using column ordinal in a mapping for SQLServerBulkCopy operation)
* @param jdbcType
* JDBC data type of the column
* @param precision
* Precision for the column (ignored for the appropriate data types)
* @param scale
* Scale for the column (ignored for the appropriate data types)
* @throws SQLServerException
* when an error occurs
*/
public void addColumnMetadata(int positionInFile,
String name,
int jdbcType,
int precision,
int scale) throws SQLServerException {
addColumnMetadataInternal(positionInFile, name, jdbcType, precision, scale, null);
}
/**
* Adds metadata for the given column in the file.
*
* @param positionInFile
* Indicates which column the metadata is for. Columns start at 1.
* @param name
* Name for the column (optional if only using column ordinal in a mapping for SQLServerBulkCopy operation)
* @param jdbcType
* JDBC data type of the column
* @param precision
* Precision for the column (ignored for the appropriate data types)
* @param scale
* Scale for the column (ignored for the appropriate data types)
* @param dateTimeFormatter
* format to parse data that is sent
* @throws SQLServerException
* when an error occurs
*/
void addColumnMetadataInternal(int positionInFile,
String name,
int jdbcType,
int precision,
int scale,
DateTimeFormatter dateTimeFormatter) throws SQLServerException {
loggerExternal.entering(loggerClassName, "addColumnMetadata", new Object[] {positionInFile, name, jdbcType, precision, scale});
String colName = "";
if (0 >= positionInFile) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_invalidColumnOrdinal"));
Object[] msgArgs = {positionInFile};
throw new SQLServerException(form.format(msgArgs), SQLState.COL_NOT_FOUND, DriverError.NOT_SET, null);
}
if (null != name)
colName = name.trim();
else if ((columnNames != null) && (columnNames.length >= positionInFile))
colName = columnNames[positionInFile - 1];
if ((columnNames != null) && (positionInFile > columnNames.length)) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_invalidColumn"));
Object[] msgArgs = {positionInFile};
throw new SQLServerException(form.format(msgArgs), SQLState.COL_NOT_FOUND, DriverError.NOT_SET, null);
}
checkDuplicateColumnName(positionInFile, name);
switch (jdbcType) {
/*
* SQL Server supports numerous string literal formats for temporal types, hence sending them as varchar with approximate
* precision(length) needed to send supported string literals. string literal formats supported by temporal types are available in MSDN
* page on data types.
*/
case java.sql.Types.DATE:
case java.sql.Types.TIME:
case java.sql.Types.TIMESTAMP:
case microsoft.sql.Types.DATETIMEOFFSET:
// The precision is just a number long enough to hold all types of temporal data, doesn't need to be exact precision.
columnMetadata.put(positionInFile, new ColumnMetadata(colName, jdbcType, 50, scale, dateTimeFormatter));
break;
// Redirect SQLXML as LONGNVARCHAR
// SQLXML is not valid type in TDS
case java.sql.Types.SQLXML:
columnMetadata.put(positionInFile, new ColumnMetadata(colName, java.sql.Types.LONGNVARCHAR, precision, scale, dateTimeFormatter));
break;
// Redirecting Float as Double based on data type mapping
// https://msdn.microsoft.com/en-us/library/ms378878%28v=sql.110%29.aspx
case java.sql.Types.FLOAT:
columnMetadata.put(positionInFile, new ColumnMetadata(colName, java.sql.Types.DOUBLE, precision, scale, dateTimeFormatter));
break;
// redirecting BOOLEAN as BIT
case java.sql.Types.BOOLEAN:
columnMetadata.put(positionInFile, new ColumnMetadata(colName, java.sql.Types.BIT, precision, scale, dateTimeFormatter));
break;
default:
columnMetadata.put(positionInFile, new ColumnMetadata(colName, jdbcType, precision, scale, dateTimeFormatter));
}
loggerExternal.exiting(loggerClassName, "addColumnMetadata");
}
/**
* Set the format for reading in dates from the file.
*
* @param dateTimeFormat
* format to parse data sent as java.sql.Types.TIMESTAMP_WITH_TIMEZONE
*/
public void setTimestampWithTimezoneFormat(String dateTimeFormat) {
DriverJDBCVersion.checkSupportsJDBC42();
loggerExternal.entering(loggerClassName, "setTimestampWithTimezoneFormat", dateTimeFormat);
this.dateTimeFormatter = DateTimeFormatter.ofPattern(dateTimeFormat);
loggerExternal.exiting(loggerClassName, "setTimestampWithTimezoneFormat");
}
/**
* Set the format for reading in dates from the file.
*
* @param dateTimeFormatter
* format to parse data sent as java.sql.Types.TIMESTAMP_WITH_TIMEZONE
*/
public void setTimestampWithTimezoneFormat(DateTimeFormatter dateTimeFormatter) {
loggerExternal.entering(loggerClassName, "setTimestampWithTimezoneFormat", new Object[] {dateTimeFormatter});
this.dateTimeFormatter = dateTimeFormatter;
loggerExternal.exiting(loggerClassName, "setTimestampWithTimezoneFormat");
}
/**
* Set the format for reading in dates from the file.
*
* @param timeFormat
* format to parse data sent as java.sql.Types.TIME_WITH_TIMEZONE
*/
public void setTimeWithTimezoneFormat(String timeFormat) {
DriverJDBCVersion.checkSupportsJDBC42();
loggerExternal.entering(loggerClassName, "setTimeWithTimezoneFormat", timeFormat);
this.timeFormatter = DateTimeFormatter.ofPattern(timeFormat);
loggerExternal.exiting(loggerClassName, "setTimeWithTimezoneFormat");
}
/**
* Set the format for reading in dates from the file.
*
* @param dateTimeFormatter
* format to parse data sent as java.sql.Types.TIME_WITH_TIMEZONE
*/
public void setTimeWithTimezoneFormat(DateTimeFormatter dateTimeFormatter) {
loggerExternal.entering(loggerClassName, "setTimeWithTimezoneFormat", new Object[] {dateTimeFormatter});
this.timeFormatter = dateTimeFormatter;
loggerExternal.exiting(loggerClassName, "setTimeWithTimezoneFormat");
}
/**
* Releases any resources associated with the file reader.
*
* @throws SQLServerException
* when an error occurs
*/
public void close() throws SQLServerException {
loggerExternal.entering(loggerClassName, "close");
// Ignore errors since we are only cleaning up here
if (fileReader != null)
try {
fileReader.close();
}
catch (Exception e) {
}
if (sr != null)
try {
sr.close();
}
catch (Exception e) {
}
if (fis != null)
try {
fis.close();
}
catch (Exception e) {
}
loggerExternal.exiting(loggerClassName, "close");
}
public DateTimeFormatter getColumnDateTimeFormatter(int column) {
return columnMetadata.get(column).dateTimeFormatter;
}
@Override
public Set getColumnOrdinals() {
return columnMetadata.keySet();
}
@Override
public String getColumnName(int column) {
return columnMetadata.get(column).columnName;
}
@Override
public int getColumnType(int column) {
return columnMetadata.get(column).columnType;
}
@Override
public int getPrecision(int column) {
return columnMetadata.get(column).precision;
}
@Override
public int getScale(int column) {
return columnMetadata.get(column).scale;
}
@Override
public boolean isAutoIncrement(int column) {
return false;
}
@Override
public Object[] getRowData() throws SQLServerException {
if (null == currentLine)
return null;
else {
// Binary data may be corrupted
// The limit in split() function should be a negative value, otherwise trailing empty strings are discarded.
// Empty string is returned if there is no value.
String[] data = currentLine.split(delimiter, -1);
// Cannot go directly from String[] to Object[] and expect it to act as an array.
Object[] dataRow = new Object[data.length];
for (Entry pair : columnMetadata.entrySet()) {
ColumnMetadata cm = pair.getValue();
// Reading a column not available in csv
// positionInFile > number of columns retrieved after split
if (data.length < pair.getKey() - 1) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_invalidColumn"));
Object[] msgArgs = {pair.getKey()};
throw new SQLServerException(form.format(msgArgs), SQLState.COL_NOT_FOUND, DriverError.NOT_SET, null);
}
// Source header has more columns than current line read
if (columnNames != null && (columnNames.length > data.length)) {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_CSVDataSchemaMismatch"));
Object[] msgArgs = {};
throw new SQLServerException(form.format(msgArgs), SQLState.COL_NOT_FOUND, DriverError.NOT_SET, null);
}
try {
if (0 == data[pair.getKey() - 1].length()) {
dataRow[pair.getKey() - 1] = null;
continue;
}
switch (cm.columnType) {
/*
* Both BCP and BULK INSERT considers double quotes as part of the data and throws error if any data (say "10") is to be
* inserted into an numeric column. Our implementation does the same.
*/
case Types.INTEGER: {
// Formatter to remove the decimal part as SQL Server floors the decimal in integer types
DecimalFormat decimalFormatter = new DecimalFormat("#");
String formatedfInput = decimalFormatter.format(Double.parseDouble(data[pair.getKey() - 1]));
dataRow[pair.getKey() - 1] = Integer.valueOf(formatedfInput);
break;
}
case Types.TINYINT:
case Types.SMALLINT: {
// Formatter to remove the decimal part as SQL Server floors the decimal in integer types
DecimalFormat decimalFormatter = new DecimalFormat("#");
String formatedfInput = decimalFormatter.format(Double.parseDouble(data[pair.getKey() - 1]));
dataRow[pair.getKey() - 1] = Short.valueOf(formatedfInput);
break;
}
case Types.BIGINT: {
BigDecimal bd = new BigDecimal(data[pair.getKey() - 1].trim());
try {
dataRow[pair.getKey() - 1] = bd.setScale(0, RoundingMode.DOWN).longValueExact();
} catch (ArithmeticException ex) {
String value = "'" + data[pair.getKey() - 1] + "'";
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_errorConvertingValue"));
throw new SQLServerException(form.format(new Object[]{value, JDBCType.of(cm.columnType)}), null, 0, ex);
}
break;
}
case Types.DECIMAL:
case Types.NUMERIC: {
BigDecimal bd = new BigDecimal(data[pair.getKey() - 1].trim());
dataRow[pair.getKey() - 1] = bd.setScale(cm.scale, RoundingMode.HALF_UP);
break;
}
case Types.BIT: {
// "true" => 1, "false" => 0
// Any non-zero value (integer/double) => 1, 0/0.0 => 0
try {
dataRow[pair.getKey() - 1] = (0 == Double.parseDouble(data[pair.getKey() - 1])) ? Boolean.FALSE : Boolean.TRUE;
} catch (NumberFormatException e) {
dataRow[pair.getKey() - 1] = Boolean.parseBoolean(data[pair.getKey() - 1]);
}
break;
}
case Types.REAL: {
dataRow[pair.getKey() - 1] = Float.parseFloat(data[pair.getKey() - 1]);
break;
}
case Types.DOUBLE: {
dataRow[pair.getKey() - 1] = Double.parseDouble(data[pair.getKey() - 1]);
break;
}
case Types.BINARY:
case Types.VARBINARY:
case Types.LONGVARBINARY:
case Types.BLOB: {
/*
* For binary data, the value in file may or may not have the '0x' prefix. We will try to match our implementation with
* 'BULK INSERT' except that we will allow 0x prefix whereas 'BULK INSERT' command does not allow 0x prefix. A BULK INSERT
* example: A sample csv file containing data for 2 binary columns and 1 row: 61,62 Table definition: create table t1(c1
* varbinary(10), c2 varbinary(10)) BULK INSERT command: bulk insert t1 from 'C:\in.csv'
* with(DATAFILETYPE='char',firstrow=1,FIELDTERMINATOR=',') select * from t1 shows 1 row with columns: 0x61, 0x62
*/
// Strip off 0x if present.
String binData = data[pair.getKey() - 1].trim();
if (binData.startsWith("0x") || binData.startsWith("0X")) {
dataRow[pair.getKey() - 1] = binData.substring(2);
} else {
dataRow[pair.getKey() - 1] = binData;
}
break;
}
case 2013: // java.sql.Types.TIME_WITH_TIMEZONE
{
DriverJDBCVersion.checkSupportsJDBC42();
OffsetTime offsetTimeValue;
// The per-column DateTimeFormatter gets priority.
if (null != cm.dateTimeFormatter)
offsetTimeValue = OffsetTime.parse(data[pair.getKey() - 1], cm.dateTimeFormatter);
else if (timeFormatter != null)
offsetTimeValue = OffsetTime.parse(data[pair.getKey() - 1], timeFormatter);
else
offsetTimeValue = OffsetTime.parse(data[pair.getKey() - 1]);
dataRow[pair.getKey() - 1] = offsetTimeValue;
break;
}
case 2014: // java.sql.Types.TIMESTAMP_WITH_TIMEZONE
{
DriverJDBCVersion.checkSupportsJDBC42();
OffsetDateTime offsetDateTimeValue;
// The per-column DateTimeFormatter gets priority.
if (null != cm.dateTimeFormatter)
offsetDateTimeValue = OffsetDateTime.parse(data[pair.getKey() - 1], cm.dateTimeFormatter);
else if (dateTimeFormatter != null)
offsetDateTimeValue = OffsetDateTime.parse(data[pair.getKey() - 1], dateTimeFormatter);
else
offsetDateTimeValue = OffsetDateTime.parse(data[pair.getKey() - 1]);
dataRow[pair.getKey() - 1] = offsetDateTimeValue;
break;
}
case Types.NULL: {
dataRow[pair.getKey() - 1] = null;
break;
}
case Types.DATE:
case Types.CHAR:
case Types.NCHAR:
case Types.VARCHAR:
case Types.NVARCHAR:
case Types.LONGVARCHAR:
case Types.LONGNVARCHAR:
case Types.CLOB:
default: {
// The string is copied as is.
/*
* Handling double quotes: Both BCP (without a format file) and BULK INSERT behaves the same way for double quotes. They
* treat double quotes as part of the data. For a CSV file as follows, data is inserted as is: ""abc"" "abc" abc a"b"c
* a""b""c Excel on the other hand, shows data as follows. It strips off beginning and ending quotes, and sometimes quotes
* get messed up. When the same CSV is saved from Excel again, Excel adds additional quotes. abc"" abc abc a"b"c a""b""c
* In our implementation we will match the behavior with BCP and BULK INSERT. BCP command: bcp table1 in in.csv -c -t , -r
* 0x0A -S localhost -U sa -P BULK INSERT command: bulk insert table1 from 'in.csv' with (FIELDTERMINATOR=',')
*
* Handling delimiters in data: Excel allows comma in data when data is surrounded with quotes. For example,
* "Hello, world" is treated as one cell. BCP and BULK INSERT deos not allow field terminators in data:
* https://technet.microsoft.com/en-us/library/aa196735%28v=sql.80%29.aspx?f=255&MSPPError=-2147217396
*/
dataRow[pair.getKey() - 1] = data[pair.getKey() - 1];
break;
}
}
} catch (IllegalArgumentException e) {
String value = "'" + data[pair.getKey() - 1] + "'";
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_errorConvertingValue"));
throw new SQLServerException(form.format(new Object[]{value, JDBCType.of(cm.columnType)}), null, 0, e);
} catch (ArrayIndexOutOfBoundsException e) {
throw new SQLServerException(SQLServerException.getErrString("R_CSVDataSchemaMismatch"), e);
}
}
return dataRow;
}
}
@Override
public boolean next() throws SQLServerException {
try {
currentLine = fileReader.readLine();
}
catch (IOException e) {
throw new SQLServerException(e.getMessage(), null, 0, e);
}
return (null != currentLine);
}
/*
* Helper method to throw a SQLServerExeption with the invalidArgument message and given argument.
*/
private void throwInvalidArgument(String argument) throws SQLServerException {
MessageFormat form = new MessageFormat(SQLServerException.getErrString("R_invalidArgument"));
Object[] msgArgs = {argument};
SQLServerException.makeFromDriverError(null, null, form.format(msgArgs), null, false);
}
/*
* Method to throw a SQLServerExeption for duplicate column names
*/
private void checkDuplicateColumnName(int positionInFile,
String colName) throws SQLServerException {
if (null != colName && colName.trim().length() != 0) {
for (Entry entry : columnMetadata.entrySet()) {
// duplicate check is not performed in case of same positionInFile value
if (null != entry && entry.getKey() != positionInFile) {
if (null != entry.getValue() && colName.trim().equalsIgnoreCase(entry.getValue().columnName)) {
throw new SQLServerException(SQLServerException.getErrString("R_BulkCSVDataDuplicateColumn"), null);
}
}
}
}
}
}