Postgres performance comparing GCP and AWS

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Postgres performance comparing GCP and AWS

Maurici Meneghetti
Hi everyone,

I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
I’ve run this query a few times to make sure both should be reading data from cache.
I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.

DETAILS:
Query explain for Postgres on GCP VM:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=18.80..2480.65 rows=799 width=70) (actual time=216.766..776.032 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5223
    Buffers: shared hit=423 read=4821
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..18.61 rows=824 width=0) (actual time=109.000..109.001 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=18
Planning time: 456.315 ms
Execution time: 776.976 ms

Query explain for Postgres on AWS RDS:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=190.02..13204.28 rows=6213 width=69) (actual time=2.215..14.505 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5209
    Buffers: shared hit=3290 read=1948
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..188.46 rows=6405 width=0) (actual time=1.159..1.159 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=26
Planning time: 0.407 ms
Execution time: 14.87 ms

PostgreSQL version number running:
• VM on GCP
: PostgreSQL 11.10 (Debian 11.10-0+deb10u1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 8.3.0-6) 8.3.0, 64-bit
• Managed by RDS on AWS: PostgreSQL 11.10 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-11), 64-bit

How PostgreSQL was installed:
• VM on GCP
: Already installed when created VM running Debian on Google Console.
• Managed by RDS on AWS: RDS managed the installation.

Changes made to the settings in the postgresql.conf file:
Here are some postgres parameters that might be useful:
Instance on VM on GCP (2 vCPUs, 2 GB memory, 800 GB disk):
• effective_cache_size: 1496MB
• maintenance_work_mem: 255462kB (close to 249MB)
• max_wal_size: 1GB
• min_wal_size: 512MB
• shared_buffers: 510920kB (close to 499MB)
• max_locks_per_transaction 1000
• wal_buffers: 15320kB (close to 15MB)
• work_mem: 2554kB
• effective_io_concurrency: 200
• dynamic_shared_memory_type: posix
On this instance we installed a postgres extension called timescaledb to gain performance on other tables. Some of these parameters were set using recommendations from that extension.

Instance managed by RDS (2 vCPUs, 2 GiB RAM, 250GB disk, 750 de IOPS):
• effective_cache_size: 1887792kB (close to 1844MB)
• maintenance_work_mem: 64MB
• max_wal_size: 2GB
• min_wal_size: 192MB
• shared_buffers: 943896kB (close to 922MB)
• max_locks_per_transaction 64

Operating system and version by runing "uname -a":
• VM on GCP:
Linux {{{my instance name}}} 4.19.0-14-cloud-amd64 #1 SMP Debian 4.19.171-2 (2021-01-30) x86_64 GNU/Linux
• Managed by AWS RDS: Aparently Red Hay as shown using SELECT version();

Program used to connect to PostgreSQL: Python psycopg2.connect() to create the connection and pandas read_sql_query() to query using that connection.

Thanks in advance
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Re: Postgres performance comparing GCP and AWS

Gunter

Hi Maurici,

in my experience the key factor about speed in big queries is sequential scan. There is a huge variance in how the system is tuned. In some cases I cannot read more than 10 MB/s, in others I get to expect 20-40 MB/s. But then, when things are tuned well and the parallel workers set in, I see the throughput spike to 100-200 MB/s.

You may have to enable the parallel workers in your postgresql.conf

So, to me, this is what you want to check first. While the query runs, have both iostat and top running, with top -j or -c or -a or whatever it is on that particular OS to see the detail info about the process. Perhaps even -H to see threads.

Then you should see good flow with high read speed and reasonable CPU load %. If you get low read speed and low CPU that is a sign of IO blockage somewhere. If you get high CPU and low IO, that's a planning mistake (the nested loop trap). You don't have that here apparently. But index scans I have seen with much worse IO throughput than seq table scans. Not sure.

Also, on AWS you need to be sure you have enough IOPS provisioned on your EBS (I use gp3 now where you can have up to 10k IOPS) and  also check bus throughput of the EC2 instance. Needless to say you don't want a t* instance where you have a limited burst CPU capacity only.

regards,
-Gunther

On 2/23/2021 1:12 PM, Maurici Meneghetti wrote:
Hi everyone,

I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
I’ve run this query a few times to make sure both should be reading data from cache.
I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.

DETAILS:
Query explain for Postgres on GCP VM:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=18.80..2480.65 rows=799 width=70) (actual time=216.766..776.032 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5223
    Buffers: shared hit=423 read=4821
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..18.61 rows=824 width=0) (actual time=109.000..109.001 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=18
Planning time: 456.315 ms
Execution time: 776.976 ms

Query explain for Postgres on AWS RDS:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=190.02..13204.28 rows=6213 width=69) (actual time=2.215..14.505 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5209
    Buffers: shared hit=3290 read=1948
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..188.46 rows=6405 width=0) (actual time=1.159..1.159 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=26
Planning time: 0.407 ms
Execution time: 14.87 ms

PostgreSQL version number running:
• VM on GCP
: PostgreSQL 11.10 (Debian 11.10-0+deb10u1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 8.3.0-6) 8.3.0, 64-bit
• Managed by RDS on AWS: PostgreSQL 11.10 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-11), 64-bit

How PostgreSQL was installed:
• VM on GCP
: Already installed when created VM running Debian on Google Console.
• Managed by RDS on AWS: RDS managed the installation.

Changes made to the settings in the postgresql.conf file:
Here are some postgres parameters that might be useful:
Instance on VM on GCP (2 vCPUs, 2 GB memory, 800 GB disk):
• effective_cache_size: 1496MB
• maintenance_work_mem: 255462kB (close to 249MB)
• max_wal_size: 1GB
• min_wal_size: 512MB
• shared_buffers: 510920kB (close to 499MB)
• max_locks_per_transaction 1000
• wal_buffers: 15320kB (close to 15MB)
• work_mem: 2554kB
• effective_io_concurrency: 200
• dynamic_shared_memory_type: posix
On this instance we installed a postgres extension called timescaledb to gain performance on other tables. Some of these parameters were set using recommendations from that extension.

Instance managed by RDS (2 vCPUs, 2 GiB RAM, 250GB disk, 750 de IOPS):
• effective_cache_size: 1887792kB (close to 1844MB)
• maintenance_work_mem: 64MB
• max_wal_size: 2GB
• min_wal_size: 192MB
• shared_buffers: 943896kB (close to 922MB)
• max_locks_per_transaction 64

Operating system and version by runing "uname -a":
• VM on GCP:
Linux {{{my instance name}}} 4.19.0-14-cloud-amd64 #1 SMP Debian 4.19.171-2 (2021-01-30) x86_64 GNU/Linux
• Managed by AWS RDS: Aparently Red Hay as shown using SELECT version();

Program used to connect to PostgreSQL: Python psycopg2.connect() to create the connection and pandas read_sql_query() to query using that connection.

Thanks in advance
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Re: Postgres performance comparing GCP and AWS

Milos Babic
In reply to this post by Maurici Meneghetti
Hi Maurici,

as a starting point: can you make sure your GPC instance is configured in the same way AWS is?
Once you do it, repeat the tests, and post the outcome.

Thanks,
Milos



On Tue, Feb 23, 2021 at 11:14 PM Maurici Meneghetti <[hidden email]> wrote:
Hi everyone,

I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
I’ve run this query a few times to make sure both should be reading data from cache.
I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.

DETAILS:
Query explain for Postgres on GCP VM:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=18.80..2480.65 rows=799 width=70) (actual time=216.766..776.032 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5223
    Buffers: shared hit=423 read=4821
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..18.61 rows=824 width=0) (actual time=109.000..109.001 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=18
Planning time: 456.315 ms
Execution time: 776.976 ms

Query explain for Postgres on AWS RDS:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=190.02..13204.28 rows=6213 width=69) (actual time=2.215..14.505 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5209
    Buffers: shared hit=3290 read=1948
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..188.46 rows=6405 width=0) (actual time=1.159..1.159 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=26
Planning time: 0.407 ms
Execution time: 14.87 ms

PostgreSQL version number running:
• VM on GCP
: PostgreSQL 11.10 (Debian 11.10-0+deb10u1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 8.3.0-6) 8.3.0, 64-bit
• Managed by RDS on AWS: PostgreSQL 11.10 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-11), 64-bit

How PostgreSQL was installed:
• VM on GCP
: Already installed when created VM running Debian on Google Console.
• Managed by RDS on AWS: RDS managed the installation.

Changes made to the settings in the postgresql.conf file:
Here are some postgres parameters that might be useful:
Instance on VM on GCP (2 vCPUs, 2 GB memory, 800 GB disk):
• effective_cache_size: 1496MB
• maintenance_work_mem: 255462kB (close to 249MB)
• max_wal_size: 1GB
• min_wal_size: 512MB
• shared_buffers: 510920kB (close to 499MB)
• max_locks_per_transaction 1000
• wal_buffers: 15320kB (close to 15MB)
• work_mem: 2554kB
• effective_io_concurrency: 200
• dynamic_shared_memory_type: posix
On this instance we installed a postgres extension called timescaledb to gain performance on other tables. Some of these parameters were set using recommendations from that extension.

Instance managed by RDS (2 vCPUs, 2 GiB RAM, 250GB disk, 750 de IOPS):
• effective_cache_size: 1887792kB (close to 1844MB)
• maintenance_work_mem: 64MB
• max_wal_size: 2GB
• min_wal_size: 192MB
• shared_buffers: 943896kB (close to 922MB)
• max_locks_per_transaction 64

Operating system and version by runing "uname -a":
• VM on GCP:
Linux {{{my instance name}}} 4.19.0-14-cloud-amd64 #1 SMP Debian 4.19.171-2 (2021-01-30) x86_64 GNU/Linux
• Managed by AWS RDS: Aparently Red Hay as shown using SELECT version();

Program used to connect to PostgreSQL: Python psycopg2.connect() to create the connection and pandas read_sql_query() to query using that connection.

Thanks in advance

 
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Re: Postgres performance comparing GCP and AWS

Julien Rouhaud
In reply to this post by Maurici Meneghetti
Hi,

On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
<[hidden email]> wrote:

>
> I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> I’ve run this query a few times to make sure both should be reading data from cache.
> I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
>
> DETAILS:
> [...]
> Planning time: 456.315 ms
> Execution time: 776.976 ms
>
> Query explain for Postgres on AWS RDS:
> [...]
> Planning time: 0.407 ms
> Execution time: 14.87 ms

Those queries were executed in respectively ~1s and ~15ms (one thing
to note is that the slower one had less data in cache, which may or
may note account for the difference).  Does those plans reflect the
reality of your slow executions?  If yes it's likely due to quite slow
network transfer.  Otherwise we would need an explain plan from the
slow execution, for which auto_explain can help you.  See
https://www.postgresql.org/docs/11/auto-explain.html for more details.


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Re: Postgres performance comparing GCP and AWS

Igor Gois
Hi, Julien

Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.

Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.

image.png

Thanks in advance

Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
Hi,

On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
<[hidden email]> wrote:
>
> I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> I’ve run this query a few times to make sure both should be reading data from cache.
> I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
>
> DETAILS:
> [...]
> Planning time: 456.315 ms
> Execution time: 776.976 ms
>
> Query explain for Postgres on AWS RDS:
> [...]
> Planning time: 0.407 ms
> Execution time: 14.87 ms

Those queries were executed in respectively ~1s and ~15ms (one thing
to note is that the slower one had less data in cache, which may or
may note account for the difference).  Does those plans reflect the
reality of your slow executions?  If yes it's likely due to quite slow
network transfer.  Otherwise we would need an explain plan from the
slow execution, for which auto_explain can help you.  See
https://www.postgresql.org/docs/11/auto-explain.html for more details.


--
Att,

Igor Gois | Sócio Consultor
(48) 99169-9889 | Skype: igor_msg

  
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Re: Postgres performance comparing GCP and AWS

Imre Samu
In reply to this post by Maurici Meneghetti
> I expect my postgres on GPC to be at least similar to the one managed by AWS RDS

imho:
-  on Google Cloud you can test with  "Cloud SQL for Postgresql" ( https://cloud.google.com/sql/docs/postgres )
-  on Google Compute Engine ( VM ):  you have to tune the disks ; linux ; file system ; scheduler ; 
         and it is a complex task

imho:  select the perfect disk types for the postgresql data  ( and create a fast RAID )
Compute Engine offers several types of storage options for your instances. Each of the following storage options has unique price and performance characteristics:
- Zonal persistent disk: Efficient, reliable block storage.
- Regional persistent disk: Regional block storage replicated in two zones.
- Local SSD: High performance, transient, local block storage.
- Cloud Storage buckets: Affordable object storage.
- Filestore: High performance file storage for Google Cloud users.

regards,
 Imre


Maurici Meneghetti <[hidden email]> ezt írta (időpont: 2021. febr. 23., K, 23:14):
Hi everyone,

I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
I’ve run this query a few times to make sure both should be reading data from cache.
I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.

DETAILS:
Query explain for Postgres on GCP VM:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=18.80..2480.65 rows=799 width=70) (actual time=216.766..776.032 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5223
    Buffers: shared hit=423 read=4821
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..18.61 rows=824 width=0) (actual time=109.000..109.001 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=18
Planning time: 456.315 ms
Execution time: 776.976 ms

Query explain for Postgres on AWS RDS:
Bitmap Heap Scan on SignalRecordsBlobs SignalRecordsBlobs  (cost=190.02..13204.28 rows=6213 width=69) (actual time=2.215..14.505 rows=5122 loops=1)
    Filter: (("DateTime" >= \'2019-11-28 14:00:12.5402\'::timestamp without time zone) AND ("DateTime" <= \'2020-07-23 21:12:32.249\'::timestamp without time zone))
    Heap Blocks: exact=5209
    Buffers: shared hit=3290 read=1948
  ->  Bitmap Index Scan on IDX_SignalRecordsBlobs_SignalSettingId  (cost=0.00..188.46 rows=6405 width=0) (actual time=1.159..1.159 rows=5228 loops=1)
          Index Cond: ("SignalSettingId" = 103)
          Buffers: shared hit=3 read=26
Planning time: 0.407 ms
Execution time: 14.87 ms

PostgreSQL version number running:
• VM on GCP
: PostgreSQL 11.10 (Debian 11.10-0+deb10u1) on x86_64-pc-linux-gnu, compiled by gcc (Debian 8.3.0-6) 8.3.0, 64-bit
• Managed by RDS on AWS: PostgreSQL 11.10 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-11), 64-bit

How PostgreSQL was installed:
• VM on GCP
: Already installed when created VM running Debian on Google Console.
• Managed by RDS on AWS: RDS managed the installation.

Changes made to the settings in the postgresql.conf file:
Here are some postgres parameters that might be useful:
Instance on VM on GCP (2 vCPUs, 2 GB memory, 800 GB disk):
• effective_cache_size: 1496MB
• maintenance_work_mem: 255462kB (close to 249MB)
• max_wal_size: 1GB
• min_wal_size: 512MB
• shared_buffers: 510920kB (close to 499MB)
• max_locks_per_transaction 1000
• wal_buffers: 15320kB (close to 15MB)
• work_mem: 2554kB
• effective_io_concurrency: 200
• dynamic_shared_memory_type: posix
On this instance we installed a postgres extension called timescaledb to gain performance on other tables. Some of these parameters were set using recommendations from that extension.

Instance managed by RDS (2 vCPUs, 2 GiB RAM, 250GB disk, 750 de IOPS):
• effective_cache_size: 1887792kB (close to 1844MB)
• maintenance_work_mem: 64MB
• max_wal_size: 2GB
• min_wal_size: 192MB
• shared_buffers: 943896kB (close to 922MB)
• max_locks_per_transaction 64

Operating system and version by runing "uname -a":
• VM on GCP:
Linux {{{my instance name}}} 4.19.0-14-cloud-amd64 #1 SMP Debian 4.19.171-2 (2021-01-30) x86_64 GNU/Linux
• Managed by AWS RDS: Aparently Red Hay as shown using SELECT version();

Program used to connect to PostgreSQL: Python psycopg2.connect() to create the connection and pandas read_sql_query() to query using that connection.

Thanks in advance
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Re: Postgres performance comparing GCP and AWS

Philip Semanchuk-2
In reply to this post by Igor Gois


> On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
>
> Hi, Julien
>
> Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
>
> Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.

Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.

Hope this is useful.

Cheers
Philip

>
>
> Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> Hi,
>
> On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> <[hidden email]> wrote:
> >
> > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > I’ve run this query a few times to make sure both should be reading data from cache.
> > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> >
> > DETAILS:
> > [...]
> > Planning time: 456.315 ms
> > Execution time: 776.976 ms
> >
> > Query explain for Postgres on AWS RDS:
> > [...]
> > Planning time: 0.407 ms
> > Execution time: 14.87 ms
>
> Those queries were executed in respectively ~1s and ~15ms (one thing
> to note is that the slower one had less data in cache, which may or
> may note account for the difference).  Does those plans reflect the
> reality of your slow executions?  If yes it's likely due to quite slow
> network transfer.  Otherwise we would need an explain plan from the
> slow execution, for which auto_explain can help you.  See
> https://www.postgresql.org/docs/11/auto-explain.html for more details.
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>  



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Re: Postgres performance comparing GCP and AWS

Igor Gois
Hi, Philip

We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';

but it was really fast. I think the results were discarded.

AWS Execution time select without explain: 24.96505s (calculated in python client)
AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)

https://explain.depesz.com/s/5HRO

Thanks in advance

Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:


> On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
>
> Hi, Julien
>
> Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
>
> Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.

Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.

Hope this is useful.

Cheers
Philip

>
>
> Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> Hi,
>
> On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> <[hidden email]> wrote:
> >
> > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > I’ve run this query a few times to make sure both should be reading data from cache.
> > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> >
> > DETAILS:
> > [...]
> > Planning time: 456.315 ms
> > Execution time: 776.976 ms
> >
> > Query explain for Postgres on AWS RDS:
> > [...]
> > Planning time: 0.407 ms
> > Execution time: 14.87 ms
>
> Those queries were executed in respectively ~1s and ~15ms (one thing
> to note is that the slower one had less data in cache, which may or
> may note account for the difference).  Does those plans reflect the
> reality of your slow executions?  If yes it's likely due to quite slow
> network transfer.  Otherwise we would need an explain plan from the
> slow execution, for which auto_explain can help you.  See
> https://www.postgresql.org/docs/11/auto-explain.html for more details.
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>   



--
Att,

Igor Gois | Sócio Consultor
(48) 99169-9889 | Skype: igor_msg

  
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Re: Postgres performance comparing GCP and AWS

Philip Semanchuk-2


> On Feb 25, 2021, at 3:46 PM, Igor Gois <[hidden email]> wrote:
>
> Hi, Philip
>
> We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
>
> but it was really fast. I think the results were discarded.

EXPLAIN and EXPLAIN ANALYZE are different in an important way. EXPLAIN merely plans the query, EXPLAIN ANALYZE plans *and executes* the query. From the doc —

"The ANALYZE option causes the statement to be actually executed, not only planned....Keep in mind that the statement is actually executed when the ANALYZE option is used. Although EXPLAIN will discard any output that a SELECT would return, other side effects of the statement will happen as usual. “

https://www.postgresql.org/docs/12/sql-explain.html


>
> AWS Execution time select without explain: 24.96505s (calculated in python client)
> AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)
>
> https://explain.depesz.com/s/5HRO
>
> Thanks in advance
>
>
> Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:
>
>
> > On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
> >
> > Hi, Julien
> >
> > Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
> >
> > Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.
>
> Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.
>
> Hope this is useful.
>
> Cheers
> Philip
>
> >
> >
> > Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> > Hi,
> >
> > On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> > <[hidden email]> wrote:
> > >
> > > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > > I’ve run this query a few times to make sure both should be reading data from cache.
> > > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> > >
> > > DETAILS:
> > > [...]
> > > Planning time: 456.315 ms
> > > Execution time: 776.976 ms
> > >
> > > Query explain for Postgres on AWS RDS:
> > > [...]
> > > Planning time: 0.407 ms
> > > Execution time: 14.87 ms
> >
> > Those queries were executed in respectively ~1s and ~15ms (one thing
> > to note is that the slower one had less data in cache, which may or
> > may note account for the difference).  Does those plans reflect the
> > reality of your slow executions?  If yes it's likely due to quite slow
> > network transfer.  Otherwise we would need an explain plan from the
> > slow execution, for which auto_explain can help you.  See
> > https://www.postgresql.org/docs/11/auto-explain.html for more details.
> >
> >
> > --
> > Att,
> >
> > Igor Gois | Sócio Consultor
> > (48) 99169-9889 | Skype: igor_msg
> > Site | Blog | LinkedIn | Facebook | Instagram
> >
> >  
>
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>  



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Re: Postgres performance comparing GCP and AWS

Igor Gois
Philip,

The results in first email in this thread were using explain analyze.

I thought that you asked to run using only 'explain'. My bad.

The point is, the execution time with explain analyze is less the 1 second. But the actual execution time (calculated from the python client) is 24 seconds (aws) and 300+ seconds in gcp

Thank you

Em qui., 25 de fev. de 2021 às 17:53, Philip Semanchuk <[hidden email]> escreveu:


> On Feb 25, 2021, at 3:46 PM, Igor Gois <[hidden email]> wrote:
>
> Hi, Philip
>
> We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
>
> but it was really fast. I think the results were discarded.

EXPLAIN and EXPLAIN ANALYZE are different in an important way. EXPLAIN merely plans the query, EXPLAIN ANALYZE plans *and executes* the query. From the doc —

"The ANALYZE option causes the statement to be actually executed, not only planned....Keep in mind that the statement is actually executed when the ANALYZE option is used. Although EXPLAIN will discard any output that a SELECT would return, other side effects of the statement will happen as usual. “

https://www.postgresql.org/docs/12/sql-explain.html


>
> AWS Execution time select without explain: 24.96505s (calculated in python client)
> AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)
>
> https://explain.depesz.com/s/5HRO
>
> Thanks in advance
>
>
> Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:
>
>
> > On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
> >
> > Hi, Julien
> >
> > Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
> >
> > Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.
>
> Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.
>
> Hope this is useful.
>
> Cheers
> Philip
>
> >
> >
> > Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> > Hi,
> >
> > On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> > <[hidden email]> wrote:
> > >
> > > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > > I’ve run this query a few times to make sure both should be reading data from cache.
> > > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> > >
> > > DETAILS:
> > > [...]
> > > Planning time: 456.315 ms
> > > Execution time: 776.976 ms
> > >
> > > Query explain for Postgres on AWS RDS:
> > > [...]
> > > Planning time: 0.407 ms
> > > Execution time: 14.87 ms
> >
> > Those queries were executed in respectively ~1s and ~15ms (one thing
> > to note is that the slower one had less data in cache, which may or
> > may note account for the difference).  Does those plans reflect the
> > reality of your slow executions?  If yes it's likely due to quite slow
> > network transfer.  Otherwise we would need an explain plan from the
> > slow execution, for which auto_explain can help you.  See
> > https://www.postgresql.org/docs/11/auto-explain.html for more details.
> >
> >
> > --
> > Att,
> >
> > Igor Gois | Sócio Consultor
> > (48) 99169-9889 | Skype: igor_msg
> > Site | Blog | LinkedIn | Facebook | Instagram
> >
> >   
>
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>   



--
Att,

Igor Gois | Sócio Consultor
(48) 99169-9889 | Skype: igor_msg

  
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Re: Postgres performance comparing GCP and AWS

Philip Semanchuk-2


> On Feb 25, 2021, at 4:04 PM, Igor Gois <[hidden email]> wrote:
>
> Philip,
>
> The results in first email in this thread were using explain analyze.
>
> I thought that you asked to run using only 'explain'. My bad.
>
> The point is, the execution time with explain analyze is less the 1 second. But the actual execution time (calculated from the python client) is 24 seconds (aws) and 300+ seconds in gcp

Oh OK, sorry, I wasn’t following. Yes, network speed sounds like the source of the problem.

Under AWS sometimes we log into an EC2 instance if we have to run a query that generates a lot of data so that both server and client are inside AWS. If GCP has something similar to EC2, it might be an interesting experiment to run your query from there and see how much, if any, that changes the time it takes to get results.

Hope this helps
Philip



>
> Em qui., 25 de fev. de 2021 às 17:53, Philip Semanchuk <[hidden email]> escreveu:
>
>
> > On Feb 25, 2021, at 3:46 PM, Igor Gois <[hidden email]> wrote:
> >
> > Hi, Philip
> >
> > We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> >
> > but it was really fast. I think the results were discarded.
>
> EXPLAIN and EXPLAIN ANALYZE are different in an important way. EXPLAIN merely plans the query, EXPLAIN ANALYZE plans *and executes* the query. From the doc —
>
> "The ANALYZE option causes the statement to be actually executed, not only planned....Keep in mind that the statement is actually executed when the ANALYZE option is used. Although EXPLAIN will discard any output that a SELECT would return, other side effects of the statement will happen as usual. “
>
> https://www.postgresql.org/docs/12/sql-explain.html
>
>
> >
> > AWS Execution time select without explain: 24.96505s (calculated in python client)
> > AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)
> >
> > https://explain.depesz.com/s/5HRO
> >
> > Thanks in advance
> >
> >
> > Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:
> >
> >
> > > On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
> > >
> > > Hi, Julien
> > >
> > > Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
> > >
> > > Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.
> >
> > Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.
> >
> > Hope this is useful.
> >
> > Cheers
> > Philip
> >
> > >
> > >
> > > Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> > > Hi,
> > >
> > > On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> > > <[hidden email]> wrote:
> > > >
> > > > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > > > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > > > I’ve run this query a few times to make sure both should be reading data from cache.
> > > > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> > > >
> > > > DETAILS:
> > > > [...]
> > > > Planning time: 456.315 ms
> > > > Execution time: 776.976 ms
> > > >
> > > > Query explain for Postgres on AWS RDS:
> > > > [...]
> > > > Planning time: 0.407 ms
> > > > Execution time: 14.87 ms
> > >
> > > Those queries were executed in respectively ~1s and ~15ms (one thing
> > > to note is that the slower one had less data in cache, which may or
> > > may note account for the difference).  Does those plans reflect the
> > > reality of your slow executions?  If yes it's likely due to quite slow
> > > network transfer.  Otherwise we would need an explain plan from the
> > > slow execution, for which auto_explain can help you.  See
> > > https://www.postgresql.org/docs/11/auto-explain.html for more details.
> > >
> > >
> > > --
> > > Att,
> > >
> > > Igor Gois | Sócio Consultor
> > > (48) 99169-9889 | Skype: igor_msg
> > > Site | Blog | LinkedIn | Facebook | Instagram
> > >
> > >  
> >
> >
> >
> > --
> > Att,
> >
> > Igor Gois | Sócio Consultor
> > (48) 99169-9889 | Skype: igor_msg
> > Site | Blog | LinkedIn | Facebook | Instagram
> >
> >  
>
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>  



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Re: Postgres performance comparing GCP and AWS

Justin Pitts
Since this is a comparison to RDS, and the goal presumably is to make the test as even as possible, you will want to pay attention to the network IO capacity for the client and the server in both tests.

For RDS, you will be unable to run the client software locally on the server hardware, so you should plan to do the same for the GCP comparison.

What is the machine size you are using for your RDS instance? Each machine size will specify CPU and RAM along with disk and network IO capacity. 

Is your GCP VM where you are running PG ( a GCP VM is the equivalent of an EC2 instance, by the way ) roughly equivalent to that RDS instance?

Finally, is the network topology roughly equivalent? Are you performing these tests with the same region and/or availability zone?



On Thu, Feb 25, 2021 at 3:32 PM Philip Semanchuk <[hidden email]> wrote:


> On Feb 25, 2021, at 4:04 PM, Igor Gois <[hidden email]> wrote:
>
> Philip,
>
> The results in first email in this thread were using explain analyze.
>
> I thought that you asked to run using only 'explain'. My bad.
>
> The point is, the execution time with explain analyze is less the 1 second. But the actual execution time (calculated from the python client) is 24 seconds (aws) and 300+ seconds in gcp

Oh OK, sorry, I wasn’t following. Yes, network speed sounds like the source of the problem.

Under AWS sometimes we log into an EC2 instance if we have to run a query that generates a lot of data so that both server and client are inside AWS. If GCP has something similar to EC2, it might be an interesting experiment to run your query from there and see how much, if any, that changes the time it takes to get results.

Hope this helps
Philip



>
> Em qui., 25 de fev. de 2021 às 17:53, Philip Semanchuk <[hidden email]> escreveu:
>
>
> > On Feb 25, 2021, at 3:46 PM, Igor Gois <[hidden email]> wrote:
> >
> > Hi, Philip
> >
> > We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> >
> > but it was really fast. I think the results were discarded.
>
> EXPLAIN and EXPLAIN ANALYZE are different in an important way. EXPLAIN merely plans the query, EXPLAIN ANALYZE plans *and executes* the query. From the doc —
>
> "The ANALYZE option causes the statement to be actually executed, not only planned....Keep in mind that the statement is actually executed when the ANALYZE option is used. Although EXPLAIN will discard any output that a SELECT would return, other side effects of the statement will happen as usual. “
>
> https://www.postgresql.org/docs/12/sql-explain.html
>
>
> >
> > AWS Execution time select without explain: 24.96505s (calculated in python client)
> > AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)
> >
> > https://explain.depesz.com/s/5HRO
> >
> > Thanks in advance
> >
> >
> > Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:
> >
> >
> > > On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
> > >
> > > Hi, Julien
> > >
> > > Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
> > >
> > > Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.
> >
> > Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.
> >
> > Hope this is useful.
> >
> > Cheers
> > Philip
> >
> > >
> > >
> > > Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
> > > Hi,
> > >
> > > On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
> > > <[hidden email]> wrote:
> > > >
> > > > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
> > > > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
> > > > I’ve run this query a few times to make sure both should be reading data from cache.
> > > > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
> > > >
> > > > DETAILS:
> > > > [...]
> > > > Planning time: 456.315 ms
> > > > Execution time: 776.976 ms
> > > >
> > > > Query explain for Postgres on AWS RDS:
> > > > [...]
> > > > Planning time: 0.407 ms
> > > > Execution time: 14.87 ms
> > >
> > > Those queries were executed in respectively ~1s and ~15ms (one thing
> > > to note is that the slower one had less data in cache, which may or
> > > may note account for the difference).  Does those plans reflect the
> > > reality of your slow executions?  If yes it's likely due to quite slow
> > > network transfer.  Otherwise we would need an explain plan from the
> > > slow execution, for which auto_explain can help you.  See
> > > https://www.postgresql.org/docs/11/auto-explain.html for more details.
> > >
> > >
> > > --
> > > Att,
> > >
> > > Igor Gois | Sócio Consultor
> > > (48) 99169-9889 | Skype: igor_msg
> > > Site | Blog | LinkedIn | Facebook | Instagram
> > >
> > >   
> >
> >
> >
> > --
> > Att,
> >
> > Igor Gois | Sócio Consultor
> > (48) 99169-9889 | Skype: igor_msg
> > Site | Blog | LinkedIn | Facebook | Instagram
> >
> >   
>
>
>
> --
> Att,
>
> Igor Gois | Sócio Consultor
> (48) 99169-9889 | Skype: igor_msg
> Site | Blog | LinkedIn | Facebook | Instagram
>
>   



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Re: Postgres performance comparing GCP and AWS

Hannu Krosing-7
Have you tried to set the instance running on GCP to have similar
shared_buffers as the AWS database ?

What you described has a much lower cache hit rate on GCS and 2X the
shared buffers on AWS which could well explain much of the difference
in execution times.

DETAILS:
Query explain for Postgres on GCP VM:
    Buffers: shared hit=423 read=4821

Query explain for Postgres on AWS RDS:
    Buffers: shared hit=3290 read=1948

and the configuration :

Instance on VM on GCP (2 vCPUs, 2 GB memory, 800 GB disk):
• shared_buffers: 510920kB (close to 499MB)

Instance managed by RDS (2 vCPUs, 2 GiB RAM, 250GB disk, 750 de IOPS):
• shared_buffers: 943896kB (close to 922MB)


Cheers
Hannu

On Fri, Feb 26, 2021 at 9:16 AM Justin Pitts <[hidden email]> wrote:

>
> Since this is a comparison to RDS, and the goal presumably is to make the test as even as possible, you will want to pay attention to the network IO capacity for the client and the server in both tests.
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> For RDS, you will be unable to run the client software locally on the server hardware, so you should plan to do the same for the GCP comparison.
>
> What is the machine size you are using for your RDS instance? Each machine size will specify CPU and RAM along with disk and network IO capacity.
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> Is your GCP VM where you are running PG ( a GCP VM is the equivalent of an EC2 instance, by the way ) roughly equivalent to that RDS instance?
>
> Finally, is the network topology roughly equivalent? Are you performing these tests with the same region and/or availability zone?
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>
>
> On Thu, Feb 25, 2021 at 3:32 PM Philip Semanchuk <[hidden email]> wrote:
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>> > On Feb 25, 2021, at 4:04 PM, Igor Gois <[hidden email]> wrote:
>> >
>> > Philip,
>> >
>> > The results in first email in this thread were using explain analyze.
>> >
>> > I thought that you asked to run using only 'explain'. My bad.
>> >
>> > The point is, the execution time with explain analyze is less the 1 second. But the actual execution time (calculated from the python client) is 24 seconds (aws) and 300+ seconds in gcp
>>
>> Oh OK, sorry, I wasn’t following. Yes, network speed sounds like the source of the problem.
>>
>> Under AWS sometimes we log into an EC2 instance if we have to run a query that generates a lot of data so that both server and client are inside AWS. If GCP has something similar to EC2, it might be an interesting experiment to run your query from there and see how much, if any, that changes the time it takes to get results.
>>
>> Hope this helps
>> Philip
>>
>>
>>
>> >
>> > Em qui., 25 de fev. de 2021 às 17:53, Philip Semanchuk <[hidden email]> escreveu:
>> >
>> >
>> > > On Feb 25, 2021, at 3:46 PM, Igor Gois <[hidden email]> wrote:
>> > >
>> > > Hi, Philip
>> > >
>> > > We ran: EXPLAIN (FORMAT JSON) SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
>> > >
>> > > but it was really fast. I think the results were discarded.
>> >
>> > EXPLAIN and EXPLAIN ANALYZE are different in an important way. EXPLAIN merely plans the query, EXPLAIN ANALYZE plans *and executes* the query. From the doc —
>> >
>> > "The ANALYZE option causes the statement to be actually executed, not only planned....Keep in mind that the statement is actually executed when the ANALYZE option is used. Although EXPLAIN will discard any output that a SELECT would return, other side effects of the statement will happen as usual. “
>> >
>> > https://www.postgresql.org/docs/12/sql-explain.html
>> >
>> >
>> > >
>> > > AWS Execution time select without explain: 24.96505s (calculated in python client)
>> > > AWS Execution time select with explain but without analyze: 0.03876s (calculated in python client)
>> > >
>> > > https://explain.depesz.com/s/5HRO
>> > >
>> > > Thanks in advance
>> > >
>> > >
>> > > Em qui., 25 de fev. de 2021 às 15:13, Philip Semanchuk <[hidden email]> escreveu:
>> > >
>> > >
>> > > > On Feb 24, 2021, at 10:11 AM, Igor Gois <[hidden email]> wrote:
>> > > >
>> > > > Hi, Julien
>> > > >
>> > > > Your hypothesis about network transfer makes sense. The query returns a big size byte array blobs.
>> > > >
>> > > > Is there a way to test the network speed against the instances? I have access to the network speed in gcp (5 Mb/s), but don't have access in aws rds.
>> > >
>> > > Perhaps what you should run is EXPLAIN ANALYZE SELECT...? My understanding is that EXPLAIN ANALYZE executes the query but discards the results. That doesn’t tell you the network speed of  your AWS instance, but it does isolate the query execution speed (which is what I think you’re trying to measure) from the network speed.
>> > >
>> > > Hope this is useful.
>> > >
>> > > Cheers
>> > > Philip
>> > >
>> > > >
>> > > >
>> > > > Em qua., 24 de fev. de 2021 às 10:35, Julien Rouhaud <[hidden email]> escreveu:
>> > > > Hi,
>> > > >
>> > > > On Wed, Feb 24, 2021 at 6:14 AM Maurici Meneghetti
>> > > > <[hidden email]> wrote:
>> > > > >
>> > > > > I have 2 postgres instances created from the same dump (backup), one on a GCP VM and the other on AWS RDS. The first instance takes 18 minutes and the second one takes less than 20s to run this simples query:
>> > > > > SELECT "Id", "DateTime", "SignalRegisterId", "Raw" FROM "SignalRecordsBlobs" WHERE "SignalSettingId" = 103 AND "DateTime" BETWEEN '2019-11-28T14:00:12.540200000' AND '2020-07-23T21:12:32.249000000';
>> > > > > I’ve run this query a few times to make sure both should be reading data from cache.
>> > > > > I expect my postgres on GPC to be at least similar to the one managed by AWS RDS so that I can work on improvements parallelly and compare.
>> > > > >
>> > > > > DETAILS:
>> > > > > [...]
>> > > > > Planning time: 456.315 ms
>> > > > > Execution time: 776.976 ms
>> > > > >
>> > > > > Query explain for Postgres on AWS RDS:
>> > > > > [...]
>> > > > > Planning time: 0.407 ms
>> > > > > Execution time: 14.87 ms
>> > > >
>> > > > Those queries were executed in respectively ~1s and ~15ms (one thing
>> > > > to note is that the slower one had less data in cache, which may or
>> > > > may note account for the difference).  Does those plans reflect the
>> > > > reality of your slow executions?  If yes it's likely due to quite slow
>> > > > network transfer.  Otherwise we would need an explain plan from the
>> > > > slow execution, for which auto_explain can help you.  See
>> > > > https://www.postgresql.org/docs/11/auto-explain.html for more details.
>> > > >
>> > > >
>> > > > --
>> > > > Att,
>> > > >
>> > > > Igor Gois | Sócio Consultor
>> > > > (48) 99169-9889 | Skype: igor_msg
>> > > > Site | Blog | LinkedIn | Facebook | Instagram
>> > > >
>> > > >
>> > >
>> > >
>> > >
>> > > --
>> > > Att,
>> > >
>> > > Igor Gois | Sócio Consultor
>> > > (48) 99169-9889 | Skype: igor_msg
>> > > Site | Blog | LinkedIn | Facebook | Instagram
>> > >
>> > >
>> >
>> >
>> >
>> > --
>> > Att,
>> >
>> > Igor Gois | Sócio Consultor
>> > (48) 99169-9889 | Skype: igor_msg
>> > Site | Blog | LinkedIn | Facebook | Instagram
>> >
>> >
>>
>>
>>