23%
02.06.2020
754 pages of about 63MB) with details on where to find the latest release. In my case, this was version 19.11.480. The docs are also now public, which is more convenient (an access token attached
23%
11.10.2016
psutil module - this is needed for this application.";
09 print "Exiting..."
10 sys.exit();
11 # end if
12
13
14 try:
15 import matplotlib.pyplot as plt; # Needed for plots
16 except:
17
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18.07.2013
backend3.example.com server;
05 backend4.example.com server down;
06 backend5.example.com backup server;
07 }
08
09 upstream fallback {
10 fallback1.example.com server: 8081;
11 }
12
13
14 server {
15 %
16
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03.12.2015
_config = file
05 store_file_config = ./client.conf
06
07 store_volatile = sqlite
08 store_sqlite_volatile = ./volatile.sqlite
09
10 log = on
11 log_file = ./dhcpy6d.log
12
13 really_do_it = yes
14
15 dns
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14.08.2020
100 100 010 Pre-fail Always - 0
9 Power_On_Hours 0x0032 097 097 000 Old_age Always - 12441
12 Power_Cycle_Count 0x0032 098 098 000 Old
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17.06.2017
_schema.events_statements_summary_global_by_event_name WHERE event_name LIKE "%/savepoint";
+------------+
| COUNT_STAR |
+------------+
| 1 |
+------------+
1 row in set (0.00 sec)
Hands On
The following sections demonstrate the installation
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03.08.2023
atomically and consistently across all the involved nodes.
Here's a simple example of a transaction that involves updating the prices of two books:
BEGIN;
UPDATE books SET price = price * 0.9 WHERE title
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01.08.2019
.
Listing 4
Registry Configuration
01 version: 0.1
02 log:
03 fields:
04 service: registry
05 storage:
06 filesystem:
07 rootdirectory: /var/lib/registry
08 http:
09
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29.09.2020
_On_Hours 0x0032 097 097 000 Old_age Always - 12441
12 Power_Cycle_Count 0x0032 098 098 000 Old_age Always - 1482
177 Wear_Leveling_Count 0x0013 098
23%
02.06.2020
optimizer = tf.keras.optimizers.RMSprop(0.001)
11 model.compile(loss='mean_squared_error',
12 optimizer=optimizer,
13 metrics=['mean_absolute_error', 'mean_squared_error'])
The model is shown
