pymssql - connect for each db insert
I have a script that tails a log and processes each new line. The result from parsing may or may not be written to a database. The time between writes varies. A write could be done multiple times a second or minutes could go by before writing.
I could set up the connection strategy one of two ways:
- Open the connection once, using it for each write, reopening on failure, closing on exit
- Open and close the connection for each write
Option 2 is cleaner and in case of a db failover or other unforeseen connection issue, is more reliable. In some languages there are issues with this approach (usning up sockets, etc). Is there a reason not to connect each time using pymssql?
python pymssql
asked Nov 21 '18 at 14:34
John G
12
add a comment |
I have a script that tails a log and processes each new line. The result from parsing may or may not be written to a database. The time between writes varies. A write could be done multiple times a second or minutes could go by before writing.
I could set up the connection strategy one of two ways:
- Open the connection once, using it for each write, reopening on failure, closing on exit
- Open and close the connection for each write
Option 2 is cleaner and in case of a db failover or other unforeseen connection issue, is more reliable. In some languages there are issues with this approach (usning up sockets, etc). Is there a reason not to connect each time using pymssql?
python pymssql
asked Nov 21 '18 at 14:34
John G
12
constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13
add a comment |
I have a script that tails a log and processes each new line. The result from parsing may or may not be written to a database. The time between writes varies. A write could be done multiple times a second or minutes could go by before writing.
I could set up the connection strategy one of two ways:
- Open the connection once, using it for each write, reopening on failure, closing on exit
- Open and close the connection for each write
Option 2 is cleaner and in case of a db failover or other unforeseen connection issue, is more reliable. In some languages there are issues with this approach (usning up sockets, etc). Is there a reason not to connect each time using pymssql?
python pymssql
asked Nov 21 '18 at 14:34
John G
12
I have a script that tails a log and processes each new line. The result from parsing may or may not be written to a database. The time between writes varies. A write could be done multiple times a second or minutes could go by before writing.
I could set up the connection strategy one of two ways:
- Open the connection once, using it for each write, reopening on failure, closing on exit
- Open and close the connection for each write
Option 2 is cleaner and in case of a db failover or other unforeseen connection issue, is more reliable. In some languages there are issues with this approach (usning up sockets, etc). Is there a reason not to connect each time using pymssql?
python pymssql
python pymssql
asked Nov 21 '18 at 14:34
John G
12
asked Nov 21 '18 at 14:34
John G
12
asked Nov 21 '18 at 14:34
John G
12
asked Nov 21 '18 at 14:34
John G
12
asked Nov 21 '18 at 14:34
John G
12
12
constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13
add a comment |
constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13
constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13
add a comment |
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constantly opening and closing new connections is expensive, Option 3) make a pool of connections and just recycle once done with the operation
– aws_apprentice
Nov 21 '18 at 14:37
Hi John G, welcome to stackoverflow! Is the log located on the same server as database? How critical is the data from the log - could you check the file every 5 minut and load the difference?
– Philip
Nov 21 '18 at 14:40
Hello @Phillip, lets assume the result is time-sensitive.
– John G
Dec 31 '18 at 16:13