.NET C# プログラムから DataFlex 6.2 データ ファイルを読み取る方法を探しています。.dat基本的に、データを含むいくつかのファイルをデコードして、それから作成するだけDataTableです。
FlexODBCのような商用製品があることは知っていますが、このような比較的単純なタスクにはやり過ぎのように思えます。おそらく、誰かが無料の代替手段またはデータファイル構造のドキュメントを知っているので、16進エディターで自分で理解する必要はありませんか?
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2 に答える
1
私は最近このリンクを見つけました。いくつかのテーブルで確認しましたが、100% 大丈夫というわけではありませんが、非常に良いヒントです。
DATAFLEX 2.3B DATAFILE HEADER STRUCTURE
By Peter M. Grillo
MAINSTREAM COMPUTER CONSULTING
Following is the structure of the DataFlex .DAT file for 2.3. Data
Access Corporation has deemed the structure of the .DAT file as
proprietary. The following definition of a 2.3 .DAT file was derived
independently by myself and any problem arising from the use of this
information will be your problem. Please do not call DAC and snivel. Use
at own risk. Please do not upload this to DAC's BBS.
DAC has indicated to me that I can release this information providing I
include the prior disclaimer.
All that aside, this is everything I know about a DataFlex .DAT file.
The overall layout of a 2.3 .DAT file is header, null record and data.
The header contains information about the file definition. Just about
everything you define in DFFILE can be found in the header except for
tag names. It is possible to read the header of a 2.3 .DAT file and the
corresponding .TAG file to produce a perfect .DEF file.
The following show offsets into the header:
(LSB = Least significant byte)
(MSBT = Most significant bit)
DECIMAL HEX DESCRIPTION
01 - 04 00 - 03 HIGHEST RECORD COUNT EVER (LSB FIRST)
09 - 12 08 - 0B RECORD COUNT (LSB FIRST)
13 - 16 0C - 0F MAXIMUM NUMBER OF RECORDS (LSB FIRST)
79 - 80 4E - 4F RECORD LENGTH (LSB FIRST)
89 58 DELETED SPACE (1=REUSED, 0=NOT REUSED)
90 59 NUMBER OF FIELDS
93 5C MULTIUSER REREAD (1=ACTIVE, 0=INACTIVE)
101 64 NUMBER OF FIELDS IN INDEX 1 (MSBT SET 1 IF BATCH)
102-108 65 - 6B FIELD SEGMENTS OF INDEX 1
109 6C NUMBER OF FIELDS IN INDEX 2 (MSBT SET 1 IF BATCH)
110-116 6D - 73 FIELD SEGMENTS OF INDEX 2
117 74 NUMBER OF FIELDS IN INDEX 3 (MSBT SET 1 IF BATCH)
118-124 75 - 7B FIELD SEGMENTS OF INDEX 3
125 7C NUMBER OF FIELDS IN INDEX 4 (MSBT SET 1 IF BATCH)
126-132 7D - 83 FIELD SEGMENTS OF INDEX 4
133 84 NUMBER OF FIELDS IN INDEX 5 (MSBT SET 1 IF BATCH)
134-140 85 - 8B FIELD SEGMENTS OF INDEX 5
141 8C NUMBER OF FIELDS IN INDEX 6 (MSBT SET 1 IF BATCH)
142-148 8D - 93 FIELD SEGMENTS OF INDEX 6
149 94 NUMBER OF FIELDS IN INDEX 7 (MSBT SET 1 IF BATCH)
150-156 95 - 9B FIELD SEGMENTS OF INDEX 7
157 9C NUMBER OF FIELDS IN INDEX 8 (MSBT SET 1 IF BATCH)
158-162 9D - A3 FIELD SEGMENTS OF INDEX 8
163 A4 NUMBER OF FIELDS IN INDEX 9 (MSBT SET 1 IF BATCH)
164-170 A5 - AB FIELD SEGMENTS OF INDEX 9
171 AC NUMBER OF FIELDS IN INDEX 10 (MSBT SET 1 IF BATCH)
172-108 AD - B3 FIELD SEGMENTS OF INDEX 10
181 -183 B4 - BC FILE ROOT NAME (NULL TERMINATED)
START OF FIELD DEFINITIONS.
REPEAT FOR EACH FIELD.
197-198 C4 - C5 FIELD OFFSET (LSB FIRST)
199 C6 MSBT=MAIN INDEX, LSBT=(DECIMAL POINTS/2)
200 C7 FIELD LENGTH
201 C8 FIELD TYPE 00=ASCII, 01=NUMERIC, 02=DATE, 03=OVERLAP
202 C9 RELATES TO FILE NUMBER
203-204 CA - CB RELATES TO FIELD NUMBER (LSB FIRST)
...-... .. - .. (REPEAT FOR EACH FIELD)
The null record follows the header and usually contains 00h's. The
number of bytes in the null record corresponds to the record length of
the file. The null record is record number zero.
The data that follows are records in order of record number. The number
of bytes in each record corresponds to the record length. Records are
grouped together by blocks of 512 bytes. Not every record length,
however, divides evenly into 512 so you get the occurrence of fill bytes
or 0FFh's to round out a group of records to 512 bytes. Consider the
following:
Record Length Layout
128 Divides into 512 evenly so no fill
bytes are used
170 Divided by 512 is 3 with a remainder
of 2 so after every 3 records
(starting at record 0) the are 2 fill
bytes (0FFh's)
Here is a table of common record lengths:
Record Length Records in 512 Group Number of Fill Bytes
256 2 0
170 3 2
128 4 0
102 5 2
85 6 2
73 7 1
64 8 0
56 9 8
51 10 2
46 11 6
42 12 8
39 13 5
36 14 8
34 15 2
32 16 0
30 17 2
28 18 8
26 19 18
25 20 12
24 21 8
23 22 6
22 23 6
21 24 8
20 25 12
19 26 18
18 28 8
17 30 2
16 32 0
15 34 2
14 36 8
13 39 5
12 42 8
11 46 6
10 51 2
9 56 8
8 64 0
> [fold] [
> [fold] [
Deleted records are filled with 00h's until reused.
DataFlex .DAT files can be opened from .FLX files using DIRECT_INPUT.
You can then use READ_BLOCK commands to read information.
Reading the FILELIST.CFG file is also much more efficient using
DIRECT_INPUT and READ_BLOCK. The first 128 bytes are fill and each
successive block of 128 bytes is a file in the list. In other words, if
you want file 15 then DIRECT_INPUT 'FILELIST.CFG' and READ_BLOCK off
(15*128) bytes. This would point you to the block for file 15. From
there you can read off bytes to find the Root Name, Description, and
DataFlex Name using the following layout.
> [fold] ]
> [fold] ]
DECIMAL HEX DESCRIPTION
01 - 41 00 - 28 FILE ROOT NAME (NULL TERMINATED)
42 - 74 29 - 49 FILE DESCRIPTION (NULL TERMINATED)
75 - 128 4A - 7F DATAFLEX FILE NAME (NULL TERMINATED)
> [fold] 2
私がデコードしているファイル (テーブル バージョン 3.0) には、レコード長がなく、フィールド リストがオフセットから始まり、2E0レコード間のギャップ20が00. また、レコードは 512 に整列されませんが、レコード サイズは 128 増加します。ゼロ レコードは から始まりC00ます。整列されたレコードのサイズは のように計算できます(FileSize - C00)/RecordCount。しかし、正しい方法は、0x9A位置から として読み取ることuintです。A5フィールド数があります。
データ型について:
日付は、BCD 形式で 3 バイトを使用して組み込みデータベースに格納されます。min date からの日数を表す BCD 数値です。700000を表し1642-09-17ているので、この数はベースとして役立ちます。
数値: 数値 510000001 は のよう15 10 00 00 01に保存され、16 進エディターで非常によく読み取れます。
DAT ファイルを解析して DataTable C# にするコード スニペットを次に示します。
using System;
using System.Collections.Generic;
using System.Text;
using System.IO;
using System.Data;
using System.Linq;
namespace DataFlex
{
/// <summary>
/// Classes for parsing DataFlex DAT files version 3.0
/// </summary>
public enum DFFieldType
{
ASCII = 0,
Numeric = 1,
Date = 2,
Overlap = 3,
Unknown = 4
}
public class DFField
{
public DFFieldType Type;
public Type DataType;
public int Position;
public byte Length;
public decimal Precision;
public string Name;
private Byte[] _input;
public DFField(byte[] input, string name)
{
_input = input;
Name = name;
UInt16 helper = BitConverter.ToUInt16(input, 0);
Position = helper;
helper = (ushort)((input[2] & 0x0F) * 2);
if (helper > 0)
Precision = (decimal)Math.Pow(10, helper);
else
Precision = 0;
Length = input[3];
switch (input[4])
{
case 0: Type = DFFieldType.ASCII; DataType = typeof(string); break;
case 1: Type = DFFieldType.Numeric; DataType = typeof(decimal); break;
case 2: Type = DFFieldType.Date; DataType = typeof(DateTime); break;
case 3: Type = DFFieldType.Overlap; DataType = typeof(object); break;
default: Type = DFFieldType.Unknown; break;
}
}
}
public class DFRow
{
public object[] _values;
public DFTable _DFTable;
public object[] Values { get { return _values; } }
public DFRow(byte[] input, DFTable dFTable)
{
_DFTable = dFTable;
_values = new object[dFTable.Fields.Length];
for (int i = 0; i < dFTable.Fields.Length; i++)
{
var f = dFTable.Fields[i];
object o;
switch (f.Type)
{
case DFFieldType.Date: o = BCDToDate(input, f.Position - 1, f.Length); break;
case DFFieldType.Numeric: o = BCDToDecimal(input, f.Precision, f.Position - 1, f.Length, true); break;
default: o = System.Text.Encoding.GetEncoding("ibm852").GetString(input, f.Position - 1, f.Length).TrimEnd(); break;
}
_values[i] = o;
}
}
private decimal BCDToDecimal(byte[] input, decimal precision, int start, int length, bool signed)
{
decimal result = 0;
uint i = 0;
for (i = 0; i < length; i++)
{
if (i > 0 || !signed)
{
result *= 100;
result += (decimal)(10 * (input[start + i] >> 4));
}
else
{
result *= 10;
}
result += (decimal)(input[start + i] & 0xf);
}
if (precision > 0)
result = (result / precision);
return (result);
}
private DateTime? BCDToDate(byte[] input, int start, int length)
{
DateTime baseDate = new DateTime(1642, 09, 14);
decimal baseNumber = 700000;
decimal dn = BCDToDecimal(input, 0, start, length, false);
dn = dn - baseNumber;
DateTime? result = null;
if (dn > 0)
{
result = baseDate.AddDays((double)dn);
}
return result;
}
}
public class DFTable
{
private long _beginning = 0xC00;
private UInt32 _RecordCount;
private DFField[] _Fields;
private List<DFRow> _Rows;
private UInt16 _RecordLength = 0;
private byte _FieldCount = 0;
private string[] _tags = null;
public DFField[] Fields
{
get { return _Fields; }
}
public List<DFRow> Rows
{
get { return _Rows; }
}
public DFRow LastRecord
{
get { return Rows[Rows.Count-1]; }
}
public DFTable(Stream datStream, bool readLastRecordOnly, string tagFile, string tableName)
{
if (File.Exists(tagFile))
_tags = File.ReadLines(tagFile).ToArray();
//Parsing header
byte[] input = new byte[4];
datStream.Read(input, 0, 4);
_RecordCount = BitConverter.ToUInt32(input, 0);
datStream.Seek(0x9A, SeekOrigin.Begin);
datStream.Read(input, 0, 2);
_RecordLength= BitConverter.ToUInt16(input, 0);
datStream.Seek(0xA5, SeekOrigin.Begin);
datStream.Read(input, 0, 1);
_FieldCount = input[0];
datStream.Seek(0x2E0, SeekOrigin.Begin);
_Fields = new DFField[_FieldCount];
//Parsing structure
int i;
for (i = 0; i < _FieldCount; i++)
{
input = new byte[8];
datStream.Read(input, 0, 8);
string name = _tags == null || _tags.Length<=i ? "F" + i.ToString() : _tags[i];
_Fields[i] = (new DFField(input, name));
}
_beginning = 0xC00 + _RecordLength; //Allways starts at C00
_Rows = new List<DFRow>();
input = new byte[_RecordLength];
if (readLastRecordOnly)
{
for (int idx = 1; idx < _RecordCount; idx++)
{
datStream.Seek(_beginning + (_RecordCount - idx) * _RecordLength, SeekOrigin.Begin); //Set the last record
datStream.Read(input, 0, _RecordLength);
if (input.Any(x => x != 0)) //Not deleted - not all zeroes
{
_Rows.Add(new DFRow(input, this));
break;
}
}
}
else
{
datStream.Seek(_beginning, SeekOrigin.Begin); //Go to beginning
for (int row = 0; row < _RecordCount; row ++)
{
datStream.Read(input, 0, _RecordLength);
if (input.Any(x=>x!=0)) //Not deleted
_Rows.Add(new DFRow(input, this));
}
}
}
/// <summary>
/// Převede na DataTable
/// </summary>
/// <returns></returns>
public DataTable ToDataTable()
{
DataTable dt = new DataTable();
DataColumn dc;
for (int i=0; i< this.Fields.Length; i++)
{
var f = this.Fields[i];
dc = new DataColumn(f.Name, f.DataType );
dt.Columns.Add(dc);
}
//Záznamy od prvního
foreach (var r in this.Rows)
{
DtaRow dr = dt.NewRow();
int j = 0;
foreach (object v in r.Values)
{
dr[j] = v ?? DBNull.Value;
j++;
}
dt.Rows.Add(dr);
}
return dt;
}
/// <summary>
/// https://stackoverflow.com/a/4959869/2224701
/// </summary>
/// <param name="dt"></param>
/// <param name="csvFileName"></param>
public void SaveAsCSV(string csvFileName, bool header)
{
StringBuilder sb = new StringBuilder();
if (header)
{
IEnumerable<string> columnNames = this.Fields.
Select(column => column.Name);
sb.AppendLine(string.Join(",", columnNames));
}
foreach (DFRow row in this.Rows)
{
IEnumerable<string> fields = row.Values.Select(field =>
string.Concat("\"", field!=null ? (field is DateTime ? ((DateTime)field).ToShortDateString() : field.ToString()).Replace("\"", "\"\"") : "", "\""));
sb.AppendLine(string.Join(",", fields));
}
File.WriteAllText(csvFileName, sb.ToString());
}
}
}
使い方はこんな感じです。
string fileToRead = @"D:\Table.DAT";
MemoryStream msAla = new MemoryStream(File.ReadAllBytes(fileToRead));
DFTable dft = new DFTable(msAla, false, tagFile, tname);
DataTable dt = dft.ToDataTable();
于 2017-09-03T15:25:24.440 に答える
0
それを行うためのオープンソースライブラリは知りません。「1 回限り」の場合は、VDF データベースを SQL データベースにエクスポートできる「 Visual DataPump 」を試してみてください。無料ではありませんが、小さなものであれば評価版が動作するはずです (少なくとも 60 日間)。
于 2014-10-20T11:31:00.273 に答える