Mysql – Can Group By and Count on MySQL be optimized

I have a 100 million row table on MySQL. I need to count rows for certain ranges and I have the proper indices for filtering rows. Let's say a SELECT statement returns 20000 results, but all I need is the count. Is there other technique in addition to indexing that I can use? Is there another option such as Cassandra that would handle grouping and counting in a faster way?

Here's the table structure:

mysql> desc activity;
+------------------------+---------+------+-----+---------+-------+
| Field                  | Type    | Null | Key | Default | Extra |
+------------------------+---------+------+-----+---------+-------+
| Source                 | text    | YES  | MUL | NULL    |       |
| Customer               | text    | YES  | MUL | NULL    |       |
| Month                  | int(11) | YES  |     | NULL    |       |
| Day                    | int(11) | YES  |     | NULL    |       |
| Year                   | int(11) | YES  | MUL | NULL    |       |
| Time                   | text    | YES  |     | NULL    |       |
| User                   | text    | YES  |     | NULL    |       |
| TimeStamp              | date    | YES  |     | NULL    |       |
| EmailEventType         | text    | NO   |     | NULL    |       |
+------------------------+---------+------+-----+---------+-------+

Indices:

mysql> show index from activity;
+----------+------------+-----------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table    | Non_unique | Key_name              | Seq_in_index | Column_name       | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+----------+------------+-----------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| activity |          1 | idx_activity_customer |            1 | Customer          | A         |      180035 |       64 | NULL   | YES  | BTREE      |         |               |
| activity |          1 | customer_date         |            1 | Customer          | A         |      202831 |       64 | NULL   | YES  | BTREE      |         |               |
| activity |          1 | customer_date         |            2 | Year              | A         |      303263 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | customer_date         |            3 | Month             | A         |      307744 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | customer_date         |            4 | Day               | A         |     1388270 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | dates                 |            1 | Year              | A         |        1286 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | dates                 |            2 | Month             | A         |       20604 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | dates                 |            3 | Day               | A         |      146993 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | timestamp             |            1 | Year              | A         |        1554 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | timestamp             |            2 | TimeStamp         | A         |      119908 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | timestamp_customer    |            1 | Customer          | A         |      188169 |       64 | NULL   | YES  | BTREE      |         |               |
| activity |          1 | timestamp_customer    |            2 | Year              | A         |      261389 |     NULL | NULL   | YES  | BTREE      |         |               |
| activity |          1 | timestamp_customer    |            3 | TimeStamp         | A         |      743716 |     NULL | NULL   | YES  | BTREE      |         |               |
+----------+------------+-----------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
14 rows in set (0.01 sec)

Query:

mysql> SELECT Customer, 
   User, 
   Source, 
   Count(CASE 
           WHEN ( Year = 2018 
                  AND Week(TimeStamp) = 1 ) THEN Source 
           ELSE NULL 
         END) AS '2018-W1', 
   Count(CASE 
           WHEN ( Year = 2018 
                  AND Week(TimeStamp) = 2 ) THEN Source 
           ELSE NULL 
         END) AS '2018-W2', 
   Count(CASE 
           WHEN ( Year = 2018 
                  AND Week(TimeStamp) = 3 ) THEN Source 
           ELSE NULL 
         END) AS '2018-W3', 
   Count(CASE 
           WHEN ( Year = 2018 
                  AND Week(TimeStamp) = 4 ) THEN Source 
           ELSE NULL 
         END) AS '2018-W4' 
FROM   activity 

WHERE  customer LIKE 'jones%' 
       AND ( ( Year = 2018 
               AND Week(TimeStamp) = 1 ) 
              OR ( Year = 2018 
                   AND Week(TimeStamp) = 2 ) 
              OR ( Year = 2018 
                   AND Week(TimeStamp) = 3 ) 
              OR ( Year = 2018 
                   AND Week(TimeStamp) = 4 ) ) 
       AND Source IN ( 'online', 'other' ) 
GROUP  BY Source, 
          User 
ORDER  BY Customer, 
          Source; 
+-------------------------+-----------------------------------+----------+---------+---------+---------+---------+
| Customer                | User                              | Source   | 2018-W1 | 2018-W2 | 2018-W3 | 2018-W4 |
+-------------------------+-----------------------------------+----------+---------+---------+---------+---------+
| Jones corporation       | 00000000@sample.com               | OTHER    |      87 |      51 |      75 |      20 |
| Jones corporation       | 000000000000@sample.com           | OTHER    |     125 |      98 |     115 |      62 |
| Jones corporation       | 000000000000000@sample.com        | OTHER    |      30 |       0 |       0 |       0 |

...
Truncated
...

| Jones cpa               | 111111111111@sample.com           | ONLINE   |       0 |       0 |       0 |      18 |
| Jones cpa               | 1111111111@sample.com             | ONLINE   |       0 |       0 |       0 |     225 |
+-------------------------+-----------------------------------+----------+---------+---------+---------+---------+
241 rows in set (9 min 10.93 sec)

So basically the optimizer is selecting and index, but then it takes a long time to calculate only 241 rows. Each User has a small row count of each type. How should the GROUP BY fields be related to the index?