Querying the amount of redo in Oracle Database

When a database starts to churn more redo then normal, it is handy to be able to extract the amount of redo over time, to be able to plot this on a graph.  The below query allows you to extract this info 🙂

Query for redo generation

Query to obtain the amount of redo generation over time by hour and MB:

set pages 999 lines 400select to_char(trunc(first_time, 'HH24'), 'DD/MM/YYYY HH24:MI:SS') date_by_hour, sum(round(blocks*block_size/1024/1024)) CHURN_IN_MBfrom v$archived_loggroup by trunc(first_time, 'HH24')order by 1/

Output

This is the output you will get from the query:

SQL> set pages 999 lines 400
SQL> select to_char(trunc(first_time, 'HH24'), 'DD/MM/YYYY HH24:MI:SS') date_by_hour, sum(round(blocks*block_size/1024/1024)) CHURN_IN_MB
2 from v$archived_log
3 group by trunc(first_time, 'HH24')
4 order by 1
5 /

DATE_BY_HOUR CHURN_IN_MB
------------------- -----------
07/12/2018 10:00:00 2
07/12/2018 11:00:00 51
07/12/2018 12:00:00 3731
07/12/2018 13:00:00 10857
07/12/2018 14:00:00 12505
07/12/2018 15:00:00 17493
07/12/2018 16:00:00 187
07/12/2018 17:00:00 173
07/12/2018 18:00:00 185
07/12/2018 19:00:00 137
07/12/2018 20:00:00 159
07/12/2018 21:00:00 155
07/12/2018 22:00:00 157
07/12/2018 23:00:00 183
08/12/2018 00:00:00 154
08/12/2018 01:00:00 184
08/12/2018 02:00:00 179
08/12/2018 03:00:00 179
08/12/2018 04:00:00 172
08/12/2018 05:00:00 177
08/12/2018 06:00:00 174
08/12/2018 07:00:00 172
08/12/2018 08:00:00 177
08/12/2018 09:00:00 175
08/12/2018 10:00:00 175
08/12/2018 11:00:00 220
08/12/2018 12:00:00 221
08/12/2018 13:00:00 218
08/12/2018 14:00:00 216
08/12/2018 15:00:00 214
08/12/2018 16:00:00 212
08/12/2018 17:00:00 208
08/12/2018 18:00:00 213
08/12/2018 19:00:00 207
08/12/2018 20:00:00 205
08/12/2018 21:00:00 205
08/12/2018 22:00:00 202
08/12/2018 23:00:00 228
09/12/2018 00:00:00 202
09/12/2018 01:00:00 238
09/12/2018 02:00:00 212
09/12/2018 03:00:00 227
09/12/2018 04:00:00 213
09/12/2018 05:00:00 206
09/12/2018 06:00:00 221
09/12/2018 07:00:00 222
09/12/2018 08:00:00 216
09/12/2018 09:00:00 220
09/12/2018 10:00:00 216
09/12/2018 11:00:00 217
09/12/2018 12:00:00 162
09/12/2018 13:00:00 163
09/12/2018 14:00:00 163
09/12/2018 15:00:00 160
09/12/2018 16:00:00 158
09/12/2018 17:00:00 159
09/12/2018 18:00:00 161
09/12/2018 19:00:00 157
09/12/2018 20:00:00 157
09/12/2018 21:00:00 153
09/12/2018 22:00:00 153
09/12/2018 23:00:00 176
10/12/2018 00:00:00 150
10/12/2018 01:00:00 174
10/12/2018 02:00:00 168
10/12/2018 03:00:00 167
10/12/2018 04:00:00 169
10/12/2018 05:00:00 162
10/12/2018 06:00:00 168
10/12/2018 07:00:00 166
10/12/2018 08:00:00 160
10/12/2018 09:00:00 162
10/12/2018 10:00:00 141
10/12/2018 11:00:00 144
10/12/2018 12:00:00 142
10/12/2018 13:00:00 141
10/12/2018 14:00:00 142
10/12/2018 15:00:00 169
10/12/2018 16:00:00 146
10/12/2018 17:00:00 173
10/12/2018 18:00:00 177
10/12/2018 19:00:00 175
10/12/2018 20:00:00 7278
10/12/2018 21:00:00 12604
10/12/2018 22:00:00 18154
10/12/2018 23:00:00 6844
11/12/2018 00:00:00 1350
11/12/2018 01:00:00 505
11/12/2018 02:00:00 1183
11/12/2018 03:00:00 508
11/12/2018 04:00:00 1488
11/12/2018 05:00:00 7071
11/12/2018 06:00:00 16453
11/12/2018 07:00:00 7076
11/12/2018 08:00:00 17310
11/12/2018 09:00:00 8063
11/12/2018 10:00:00 12681
11/12/2018 11:00:00 3678
11/12/2018 14:00:00 6026
11/12/2018 15:00:00 15569
11/12/2018 16:00:00 7069
11/12/2018 17:00:00 11772
11/12/2018 18:00:00 10167
11/12/2018 19:00:00 6159
11/12/2018 20:00:00 16450
11/12/2018 21:00:00 4106
11/12/2018 22:00:00 10115
11/12/2018 23:00:00 10355
12/12/2018 00:00:00 3203
12/12/2018 01:00:00 5160
12/12/2018 02:00:00 14468
12/12/2018 03:00:00 6591
12/12/2018 04:00:00 1376
12/12/2018 05:00:00 4053
12/12/2018 06:00:00 7947
12/12/2018 07:00:00 12433
12/12/2018 08:00:00 1434
12/12/2018 09:00:00 663
12/12/2018 10:00:00 1511
12/12/2018 11:00:00 654
12/12/2018 12:00:00 5661
12/12/2018 13:00:00 9817
12/12/2018 14:00:00 10148
12/12/2018 15:00:00 372
12/12/2018 16:00:00 1074
12/12/2018 17:00:00 672
12/12/2018 18:00:00 1094
12/12/2018 19:00:00 391
12/12/2018 20:00:00 2403
12/12/2018 21:00:00 827
12/12/2018 22:00:00 1108
12/12/2018 23:00:00 15575
13/12/2018 00:00:00 17219
13/12/2018 01:00:00 8255
13/12/2018 02:00:00 877
13/12/2018 03:00:00 180
13/12/2018 04:00:00 1782
13/12/2018 05:00:00 5284
13/12/2018 06:00:00 16191
13/12/2018 07:00:00 6251
13/12/2018 08:00:00 14533
13/12/2018 09:00:00 8138
13/12/2018 10:00:00 12629
13/12/2018 11:00:00 9701
13/12/2018 12:00:00 9869
13/12/2018 13:00:00 9554
13/12/2018 14:00:00 7106
13/12/2018 15:00:00 15094
13/12/2018 16:00:00 8622
13/12/2018 17:00:00 671
13/12/2018 18:00:00 1094
13/12/2018 19:00:00 370
13/12/2018 20:00:00 2332
13/12/2018 21:00:00 421

154 rows selected.

SQL>

The above output can then be used to create a pivot chart in Excel 🙂

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Thanks

Zed DBA (Zahid Anwar)

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