每天自动将数据保存到 SQLite 数据库一次

Question

我有一个包含两列的简单 SQLite 数据库。

Col 1 SimpleDateFormat("yyyyDDD") 例如 2017001（2017 年 1 月 1 日）

Col 2 int 出现次数

因此，在极少数情况下，一整天都没有发生任何事件，那天没有任何东西插入我的数据库中。在这种情况下，我想填充一个零，否则在绘制我的数据时会绕过这一天。

我进行了一些研究，我正在考虑的解决方案是设置 RTC 警报，并且每 24 小时填充一次零发生行。在可能发生的事件发生时，当汇总并发送到图表时，零不会影响我的数据。如果没有出现，我会在那里有零。

是否有更优雅的解决方案退出？我没有使用安卓闹钟的经验。 RTC 警报有什么缺点吗？也许 SQLite 有一些我可以利用的功能？我愿意接受任何解决方案。

编辑

我没有提到即使在应用程序从未打开的日子里也必须添加零。这是一个重要的区别，我之前没有提到。这些行可以在应用程序启动时追溯添加（可能在关闭几天后）。感谢您迄今为止的回复。

Answer 1

这是一种无需依赖后台任务或向数据库添加额外（无用/浪费）数据的方法。

基本上，数据被提取出来，任何缺失的天数以及实际天数都被添加到MatrixCursor（可以动态构建的光标）。

主要方法是getExpandedRows，它有两个支持方法：-

• setDate（根据包含try catch的yyyyDDD格式的字符串设置java Date对象）
• 和addMatrixRow 向MatrixCursor 添加一行并将下一个日期作为java 日期返回。

getExpandedRows 以 yyyyDDDD 格式的字符串形式接受两个参数 start 和 end 日期，这些参数用于 a) 从数据库中选择适当的行 b) 驱动添加缺失的逻辑行（天）。

所有这些都在 SQLiteOpenHelper 子类 DBHelper 中：-

public class DBHelper extends SQLiteOpenHelper {

    public static final String DBNAME = "mystats";
    public static final String TBNAME = "mystats";
    public static final String COL1 = "date";
    public static final String COL2 = "value";

    SQLiteDatabase mDB;
    SimpleDateFormat sdf = new SimpleDateFormat("yyyyDDD");
    long oneday = 1000 * 60 * 60 * 24;

    DBHelper(Context context) {
        super(context, DBNAME, null, 1);
        mDB = this.getWritableDatabase();
    }

    @Override
    public void onCreate(SQLiteDatabase db) {
        String crtsql = "CREATE TABLE IF NOT EXISTS " + TBNAME + "(" +
                COL1 + " TEXT UNIQUE NOT NULL, " +
                COL2 + " INTEGER " +
                ")";
        db.execSQL(crtsql);
    }

    @Override
    public void onUpgrade(SQLiteDatabase sqLiteDatabase, int i, int i1) {

    }

    public void addData(String date, int value) {
        ContentValues cv = new ContentValues();
        cv.put(COL1,date);
        cv.put(COL2,value);
         mDB.insert(TBNAME,null,cv);
    }

    public Cursor getAllRows(String filter) {
        return mDB.query(TBNAME,null,filter,null,null,null,null);
    }

    public Cursor getExpandedRows(String startdate, String enddate) {

        Date lastdate = setDate(startdate), finishdate = setDate(enddate), currentdate = new Date(0);
        int daysinperiod = (int)((finishdate.getTime() - lastdate.getTime()) / oneday);

        // get the base data
        String filter = COL1 + " BETWEEN " + startdate + " AND " + enddate + " ";
        Cursor base = getAllRows(filter);
        Log.d("GetExpRows","Rows Extracted from base data = " + Integer.toString(base.getCount()));

        MatrixCursor mc = new MatrixCursor(new String[]{COL1,COL2},daysinperiod);
        while (base.moveToNext()) {
            currentdate = setDate(base.getString(base.getColumnIndex(COL1)));

            while (lastdate.getTime() < currentdate.getTime()) {
                lastdate = addMatrixRow(mc, lastdate, 0L);
            }
            lastdate = addMatrixRow(mc, currentdate, base.getLong(base.getColumnIndex(COL2)));

        }
        while (currentdate.getTime() <= finishdate.getTime()) {
            currentdate = addMatrixRow(mc,currentdate, 0L);
        }
        base.close();
        return mc;
    }

    private Date addMatrixRow(MatrixCursor mc, Date date, Long value) {
        mc.addRow(new Object[]{sdf.format(date.getTime()),value});
        return new Date(date.getTime() + oneday);
    }

    private Date setDate(String date) {
        Date rv = new Date(0L);
        try {
            rv = sdf.parse(date);
        } catch (Exception e) {
        }
        return rv;
    } }

为了测试 4 行添加了几天：-

• 20017001（值100），
• 2017043（值50），
• 2017150（值 17）和
• 2017364（值33）

选择了2016364-2018004这段时间进行测试。

这是用于测试的调用活动，（请注意，您可以将矩阵光标用作普通光标）。主线是 Cursor mydata = dbhlpr.getExpandedRows("2016364","2018005");

public class MainActivity extends AppCompatActivity {

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);
        DBHelper dbhlpr = new DBHelper(this);
        Cursor csr = dbhlpr.getAllRows("");
        if (csr.getCount() == 0) {
            dbhlpr.addData("2017001",100);
            dbhlpr.addData("2017035",50);
            dbhlpr.addData("2017150",17);
            dbhlpr.addData("2017364",33);
        }
        csr.close();

        Cursor mydata = dbhlpr.getExpandedRows("2016364","2018005");
        int limit = 0;
        while (mydata.moveToNext()) {
            if(limit++ > 400) {
                break;
            }
            Log.d("MYDATA","Row " + Integer.toString(mydata.getPosition()) +
                    " for Date " + mydata.getString(mydata.getColumnIndex(DBHelper.COL1)) +
                    " has Value " + Integer.toString(mydata.getInt(mydata.getColumnIndex(DBHelper.COL2)))
            );
        }
        mydata.close();
    }
}

日志的结果输出是（.......表示为简洁起见不包括类似的行）：-

10-04 12:25:18.495 6727-6727/mjt.so46550513 D/GetExpRows: Rows Extracted from base data = 4
10-04 12:25:18.505 6727-6727/mjt.so46550513 D/MYDATA: Row 0 for Date 2016364 has Value 0
10-04 12:25:18.505 6727-6727/mjt.so46550513 D/MYDATA: Row 1 for Date 2016365 has Value 0
10-04 12:25:18.505 6727-6727/mjt.so46550513 D/MYDATA: Row 2 for Date 2016366 has Value 0
10-04 12:25:18.505 6727-6727/mjt.so46550513 D/MYDATA: Row 3 for Date 2017001 has Value 100
10-04 12:25:18.505 6727-6727/mjt.so46550513 D/MYDATA: Row 4 for Date 2017002 has Value 0
.......
10-04 12:25:18.506 6727-6727/mjt.so46550513 D/MYDATA: Row 36 for Date 2017034 has Value 0
10-04 12:25:18.506 6727-6727/mjt.so46550513 D/MYDATA: Row 37 for Date 2017035 has Value 50
10-04 12:25:18.506 6727-6727/mjt.so46550513 D/MYDATA: Row 38 for Date 2017036 has Value 0
10-04 12:25:18.506 6727-6727/mjt.so46550513 D/MYDATA: Row 39 for Date 2017037 has Value 0
....
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 151 for Date 2017148 has Value 0
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 152 for Date 2017149 has Value 0
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 153 for Date 2017150 has Value 17
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 154 for Date 2017151 has Value 0
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 155 for Date 2017152 has Value 0
10-04 12:25:18.508 6727-6727/mjt.so46550513 D/MYDATA: Row 156 for Date 2017153 has Value 0
.......
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 365 for Date 2017362 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 366 for Date 2017363 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 367 for Date 2017364 has Value 33
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 368 for Date 2017364 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 369 for Date 2017365 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 370 for Date 2018001 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 371 for Date 2018002 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 372 for Date 2018003 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 373 for Date 2018004 has Value 0
10-04 12:25:18.510 6727-6727/mjt.so46550513 D/MYDATA: Row 374 for Date 2018005 has Value 0

注意！您可能会包括改进的错误/异常处理，尤其是对于字符串到日期的转换，因为这是一个原则示例