java - 安卓 : Calculate sum and group by month (SQLite)

Question

是否有任何选项可以选择金额、按月分组并计算总和。我试图获取每个月的总和并将其传递给 ArrayList。
数据示例:

Amount    Date
230       04/03/19
500       05/03/19
400       04/04/19
600       06/04/19
100       04/03/19
...       ...

我的代码结构

private String CREATE_BILLS_TABLE = "CREATE TABLE " + TABLE_BILLS + "("
            + COLUMN_BILL_ID + " INTEGER PRIMARY KEY AUTOINCREMENT,"
            + COLUMN_BILL_USER_ID + " INTEGER,"
            + COLUMN_DESCRIPTION + " TEXT,"
            + COLUMN_AMOUNT + " INTEGER,"
            + COLUMN_DATE_STRING + " TEXT,"
            + COLUMN_COMPANY_NAME + " TEXT,"
            + COLUMN_CATEGORY + " TEXT,"
            + " FOREIGN KEY ("+COLUMN_BILL_USER_ID+") REFERENCES "+TABLE_USER+"("+COLUMN_USER_ID+"));";

 public ArrayList<Bills> getDateByUserID(int userID){
        SQLiteDatabase db = this.getReadableDatabase();
        // sorting orders
        ArrayList<Bills> listBillsDates = new ArrayList<Bills>();

        Cursor cursor = db.query(TABLE_BILLS, new String[] { COLUMN_BILL_ID,
                        COLUMN_BILL_USER_ID, COLUMN_DESCRIPTION, COLUMN_AMOUNT, COLUMN_DATE_STRING, COLUMN_COMPANY_NAME, COLUMN_CATEGORY}, COLUMN_BILL_USER_ID + "=?",
                new String[] { String.valueOf(userID) }, COLUMN_DATE_STRING, null, null, null);
        if (cursor.moveToFirst()) {
            do {
                Bills bills = new Bills();
                bills.setAmount(cursor.getInt(cursor.getColumnIndex(COLUMN_AMOUNT)));
                bills.setDateString(cursor.getString(cursor.getColumnIndex(COLUMN_DATE_STRING)));
                // Adding record to list
                listBillsDates.add(bills);
            } while (cursor.moveToNext());
        }
        cursor.close();
        db.close();

        // return category list
        return listBillsDates;
    }

Answer 1

我相信查询基于:-

SELECT sum(COLUMN_AMOUNT) AS Monthly_Total,substr(COLUMN_DATE_STRING,4) AS Month_and_Year
    FROM TABLE_BILLS 
    WHERE COLUMN_BILL_USER_ID = 1
  GROUP BY substr(COLUMN_DATE_STRING,4)
    ORDER BY substr(COLUMN_DATE_STRING,7,2)||substr(COLUMN_DATE_STRING,4,2)
;

• 请注意，其他列值将是任意结果，因此不能真正依赖(如果数据始终相同则很好)。因此它们没有被包括在内。

将产生您想要的结果:-

例如

使用以下命令来测试 SQL:-

DROP TABLE IF EXISTS TABLE_BILLS;
CREATE TABLE IF NOT EXISTS TABLE_BILLS (
    COLUMN_BILL_ID INTEGER PRIMARY KEY AUTOINCREMENT,
    COLUMN_BILL_USER_ID INTEGER,
    COLUMN_DESCRIPTION TEXT,
    COLUMN_AMOUNT INTEGER,
    COLUMN_DATE_STRING TEXT,
    COLUMN_COMPANY_NAME TEXT,
    COLUMN_CATEGORY TEXT)
    ;

-- Add the Testing data
INSERT INTO TABLE_BILLS (
    COLUMN_BILL_USER_ID, COLUMN_DESCRIPTION, COLUMN_AMOUNT, COLUMN_DATE_STRING, COLUMN_COMPANY_NAME,COLUMN_CATEGORY)
VALUES 
        (1,'blah',230,'04/03/19','cmpny','category')
        ,(1,'blah',500,'05/03/19','cmpny','category')
        ,(1,'blah',400,'04/04/19','cmpny','category')
        ,(1,'blah',600,'06/04/19','cmpny','category')
        ,(1,'blah',100,'04/03/19','cmpny','category')

        -- Extra data for another id to check exclusion
        ,(2,'blah',230,'04/03/19','cmpny','category')
        ,(2,'blah',500,'05/03/19','cmpny','category')
        ,(2,'blah',400,'04/04/19','cmpny','category')
        ,(2,'blah',600,'06/04/19','cmpny','category')
        ,(2,'blah',100,'04/03/19','cmpny','category')
;

SELECT sum(COLUMN_AMOUNT) AS Monthly_Total,substr(COLUMN_DATE_STRING,4) AS Month_and_Year
    FROM TABLE_BILLS 
    WHERE COLUMN_BILL_USER_ID = 1
  GROUP BY substr(COLUMN_DATE_STRING,4)
    ORDER BY substr(COLUMN_DATE_STRING,7,2)||substr(COLUMN_DATE_STRING,4,2)
;

结果 ID:-

然后可以将上述内容转换为由 SQLiteDatabase 查询方法使用。所以你的方法可能是这样的:-

public ArrayList<Bills> getDateByUserID(int userID) {
    SQLiteDatabase db = this.getReadableDatabase();
    String tmpcol_monthly_total = "Monthly_Total";
    String tmpcol_month_year = "Month_and_Year";
    String[] columns = new String[]{
            "sum(" + COLUMN_AMOUNT + ") AS " + tmpcol_monthly_total,
            "substr(" + COLUMN_DATE_STRING + ",4) AS " + tmpcol_month_year
    };
    String whereclause = COLUMN_BILL_USER_ID + "=?";
    String[] whereargs = new String[]{String.valueOf(userID)};
    String groupbyclause = "substr(" + COLUMN_DATE_STRING + ",4)";
    String orderbyclause = "substr(" + COLUMN_DATE_STRING + ",7,2)||substr(" + COLUMN_DATE_STRING + ",4,2)";
    ArrayList<Bills> listBillsDates = new ArrayList<Bills>();

    Cursor cursor = db.query(TABLE_BILLS, columns, whereclause,
            whereargs, groupbyclause, null, orderbyclause, null);
    if (cursor.moveToFirst()) {
        do {
            Bills bills = new Bills();
            bills.setAmount(cursor.getInt(cursor.getColumnIndex(tmpcol_monthly_total)));
            bills.setDateString(cursor.getString(cursor.getColumnIndex(tmpcol_month_year))); //<<<<<<<<<< NOTE data is MM/YY (otherwise which date to use? considering result will be arbrirtaryy)
            // Adding record to list
            listBillsDates.add(bills);
        } while (cursor.moveToNext());
    }
    cursor.close();
    db.close();

    // return category list
    return listBillsDates;
}

• 以上内容已经过测试并运行，并使用以下代码:-

  ArrayList<Bills> myMonthlyTotals = mDBHelper.getDateByUserID(1);
  Log.d("BILLSCOUNT","The number of bills extracted was " + String.valueOf(myMonthlyTotals.size()));
  for (Bills b: myMonthlyTotals) {
      Log.d("MONTHYLTOTAL","Monthly total for " + b.getDateString() + " was " + String.valueOf(b.getAmount()));
  
  }
  

• 在 Activity 中，日志中产生以下结果

:-

04-14 11:58:25.876 16653-16653/? D/BILLSCOUNT: The number of bills extracted was 2
04-14 11:58:25.877 16653-16653/? D/MONTHYLTOTAL: Monthly total for 03/19 was 830
04-14 11:58:25.877 16653-16653/? D/MONTHYLTOTAL: Monthly total for 04/19 was 1000

• 请考虑将有关非聚合列中的值的注释视为任意值。按照:-

• Each non-aggregate expression in the result-set is evaluated once for an arbitrarily selected row of the dataset. The same arbitrarily selected row is used for each non-aggregate expression. Or, if the dataset contains zero rows, then each non-aggregate expression is evaluated against a row consisting entirely of NULL values. SELECT - 3. Generation of the set of result rows.

根据评论，使用公认的 date formats可以使底层 SQL 更简单并且可能更高效。