From postgres documentation,
client_min_messages (enum)
Controls which message levels are sent to the client. Valid values are DEBUG5, DEBUG4, DEBUG3, DEBUG2, DEBUG1, LOG, NOTICE, WARNING, ERROR, FATAL, and PANIC. Each level includes all the levels that follow it. The later the level, the fewer messages are sent. The default is NOTICE. Note that LOG has a different rank here than in log_min_messages.
I am assuming that these messages are not the same as the results (PQResult) of the commands executed. If so, how do I read these messages through libpq? Would there be an impact of these messages on the application`s performance?
Messages are sent as a different message type on the PostgreSQL protocol, usually interleaved with the result stream. libpq sees them and picks them out, then adds them to a queue of notifications you can examine.
See the manual.
Related
These are the info logs
"2022-08-18T07:47:14.333850Z 32263817 [Note] [MY-010914] [Server] Aborted connection 32263817 to db: 'unconnected' user: 'xyz' host: '10.x.x.x' (Got an error reading communication packets)."
[Note] [MY-010914] [Server] Got packets out of order"
[Server] Got an error reading communication packets
I don't understand why I am getting this continuously on cloud sql logs also is this the reason why my db got crashed.
There are a lot of reasons that could perhaps lead to the MySQL connection packet issues.According to this thread MySQL Error Reading Communication Packets
MySQL network communication code was written under the assumption that queries are always reasonably short,and therefore can be sent to and processed by the server in one chunk, which is called a packet in MySQL terminology. The server allocates the memory for a temporary buffer to store the packet, and it requests enough to fit it entirely. This architecture requires a precaution to avoid having the server run out of memory---a cap on the size of the packet, which this option accomplishes.
The code of interest in relation to this option is found in sql/net_serv.cc. Take a look at my_net_read(), then follow the call to my_real_read() and pay particular attention to net_realloc().
This variable also limits the length of a result of many string functions. See sql/field.cc and sql/intem_strfunc.cc for details.
According to the MySQL Documentation
You can also get these errors if you send a query to the server that is incorrect or too large.you can increase the query limit by setting the server's max_allowed_packet variable, which has a default value of 1MB. You may also need to increase the maximum packet size on the client end. More information on setting the packet size is given in Section C.5.2.10, “Packet too large”.
An INSERT or REPLACE statement that inserts a great many rows can also cause these sorts of errors. Either one of these statements sends a single request to the server irrespective of the number of rows to be inserted; thus, you can often avoid the error by reducing the number of rows sent per INSERT or REPLACE.
Additionally you may have a look at this link1 & link2
I would like each subscriber server to monitor its health without accessing the publisher server
1.
I use the following code from the publisher to get the lag. Is it possible to compute the lag also from the subscriber server
SELECT
slot_name, active, confirmed_flush_lsn, pg_current_wal_lsn(),
(pg_current_wal_lsn() - confirmed_flush_lsn) AS bytes_lag
FROM pg_replication_slots;
If I use from the subscriber the following
select received_lsn, latest_end_lsn from pg_stat_subscription
I will still need the following from the publisher select pg_current_wal_lsn();
Is there a way to know the lag without accessing the publisher?
2. I have a duplicate value at one of the tables that caused the replication to stop, but
select srsubstate from pg_subscription_rel
is showing as 'r' for all tables.
How can I know which table is problematic
How can I know what is the reason that the replication stopped
3. How can a subscriber know that its logical slot or even publisher was dropped
No, you cannot get that information from the subscriber. The subscriber doesn't know what there is to receive that it has not yet received.
To figure out the cause when replication breaks, you have to look at the subscriber's log file. Yes, that is manual activity, but so is conflict resolution.
You will quickly figure out if the replication slot has been dropped, because there will be nasty error messages in the log. This is quite similar to dropped tables.
Looking out for best approach for designing my Kafka Consumer. Basically I would like to see what is the best way to avoid data loss in case there are any
exception/errors during processing the messages.
My use case is as below.
a) The reason why I am using a SERVICE to process the message is - in future I am planning to write an ERROR PROCESSOR application which would run at the end of the day, which will try to process the failed messages (not all messages, but messages which fails because of any dependencies like parent missing) again.
b) I want to make sure there is zero message loss and so I will save the message to a file in case there are any issues while saving the message to DB.
c) In production environment there can be multiple instances of consumer and services running and so there is high chance that multiple applications try to write to the
same file.
Q-1) Is writing to file the only option to avoid data loss ?
Q-2) If it is the only option, how to make sure multiple applications write to the same file and read at the same time ? Please consider in future once the error processor
is build, it might be reading the messages from the same file while another application is trying to write to the file.
ERROR PROCESSOR - Our source is following a event driven mechanics and there is high chance that some times the dependent event (for example, the parent entity for something) might get delayed by a couple of days. So in that case, I want my ERROR PROCESSOR to process the same messages multiple times.
I've run into something similar before. So, diving straight into your questions:
Not necessarily, you could perhaps send those messages back to Kafka in a new topic (let's say - error-topic). So, when your error processor is ready, it could just listen in to the this error-topic and consume those messages as they come in.
I think this question has been addressed in response to the first one. So, instead of using a file to write to and read from and open multiple file handles to do this concurrently, Kafka might be a better choice as it is designed for such problems.
Note: The following point is just some food for thought based on my limited understanding of your problem domain. So, you may just choose to ignore this safely.
One more point worth considering on your design for the service component - You might as well consider merging points 4 and 5 by sending all the error messages back to Kafka. That will enable you to process all error messages in a consistent way as opposed to putting some messages in the error DB and some in Kafka.
EDIT: Based on the additional information on the ERROR PROCESSOR requirement, here's a diagrammatic representation of the solution design.
I've deliberately kept the output of the ERROR PROCESSOR abstract for now just to keep it generic.
I hope this helps!
If you don't commit the consumed message before writing to the database, then nothing would be lost while Kafka retains the message. The tradeoff of that would be that if the consumer did commit to the database, but a Kafka offset commit fails or times out, you'd end up consuming records again and potentially have duplicates being processed in your service.
Even if you did write to a file, you wouldn't be guaranteed ordering unless you opened a file per partition, and ensured all consumers only ran on a single machine (because you're preserving state there, which isn't fault-tolerant). Deduplication would still need handled as well.
Also, rather than write your own consumer to a database, you could look into Kafka Connect framework. For validating a message, you can similarly deploy a Kafka Streams application to filter out bad messages from an input topic out into a topic to send to the DB
We have are developing an application that will receive events from various systems via a message queue (Azure) but it is just possible that some events (messages) will not arrive in the order they were sent. These events will be received and processed by a central CQRS/ES based system but my worry is that if the events are placed in the event store in the wrong order we will get garbage out (for example "order create" after "add order item").
Are typical ES systems meant to resolve this issue or are we meant to ensure that such messages are put in the right order before being pushed into the event store? If you have links to articles that back up either view it would help.
Edit: I think my description is clearly far too vague so the responses, while helpful in understanding CQRS/ES, do not quite answer my problem so I'll add a little more detail and hopefully someone will recognise the problem.
Firstly the players.
the front end web site (not actually relevant to this problem) delivers orders to the management system.
our management system which takes orders from the web site and passes them to the warehouse and is hosted on site.
the warehouse which accepts orders, fulfils them if possible and notifies us when an order is fulfilled or cannot be partially or completely fulfilled.
Linking the warehouse to the management system is a fairly thin Azure cloud based coupling. Messages from the warehouse are sent to a WCF/Soap layer in the cloud, parsed, and sent over the messages bus. Message to the warehouse are sent over the message bus and then, again in the cloud, converted into Soap calls to a server at the warehouse.
The warehouse is very careful to ensure that messages it sends have identifiers that increment without a gap so we can know when a message is missed. However when we take those messages and forward them to the management system they are transported over the message bus and could, in theory, arrive in the wrong order.
Now given that we have a sequence number in the messages we could ensure the messages are put back in the right order before they are sent to the CQRS/ES system but my questions is, is that necessary, can the ES actually be used to reorder the events into the logical order they were intended?
Each message that arrives in Service Bus is tagged with a SequenceNumber. The SequenceNumber is a monotonically increasing, gapless 64-bit integer sequence, scoped to the Queue (or Topic) that provides an absolute order criterion by arrival in the Queue. That order may different from the delivery order due to errors/aborts and exists so you can reconstitute order of arrival.
Two features in Service Bus specific to management of order inside a Queue are:
Sessions. A sessionful queue puts locks on all messages with the same SessionId property, meaning that FIFO is guaranteed for that sequence, since no messages later in the sequence are delivered until the "current" message is either processed or abandoned.
Deferral. The Defer method puts a message aside if the message cannot be processed at this time. The message can later be retrieved by its SequenceNumber, which pulls from the hidden deferral queue. If you need a place to keep track of which messages have been deferred for a session, you can put a data structure holding that information right into the message session, if you use a sessionful queue. You can then pick up that state again elsewhere on an accepted session if you, for instance, fail over processing onto a different machine.
These features have been built specifically for document workflows in Office 365 where order obviously matters quite a bit.
I would have commented on KarlM's answer but stackoverflow won't allow it, so here goes...
It sounds like you want the transport mechanism to provide transactional locking on your aggregate. To me this sounds inherently wrong.
It sounds as though the design being proposed is flawed. Having had this exact problem in the past, I would look at your constraints. Either you want to provide transactional guarantees to the website, or you want to provide them to the warehouse. You can't do both, one always wins.
To be fully distributed: If you want to provide them to the website, then the warehouse must ask if it can begin to fulfil the order. If you want to provide them to the warehouse, then the website must ask if it can cancel the order.
Hope that is useful.
For events generated from a single command handler/aggregate in an "optimistic locking" scenario, I would assume you would include the aggregate version in the event, and thus those events are implicitly ordered.
Events from multiple aggregates should not care about order, because of the transactional guarantees of an aggregate.
Check out http://cqrs.nu/Faq/aggregates , http://cqrs.nu/Faq/command-handlers and related FAQs
For an intro to ES and optimistic locking, look at http://www.jayway.com/2013/03/08/aggregates-event-sourcing-distilled/
You say:
"These events will be received and processed by a central CQRS/ES based system but my worry is that if the events are placed in the event store in the wrong order we will get garbage out (for example "order create" after "add order item")."
There seems to be a misunderstanding about what CQRS pattern with Event Sourcing is.
Simply put Event Sourcing means that you change Aggregates (as per DDD terminology) via internally generated events, the Aggregate persistence is represented by events and the Aggregate can be restored by replaying events. This means that the scope is quite small, the Aggregate itself.
Now, CQRS with Event Sourcing means that these events from the Aggregates are published and used to create Read projections, or other domain models that have different purposes.
So I don't really get your question given the explanations above.
Related to Ordering:
there is already an answer mentioning optimistic locking, so events generated inside a single Aggregate must be ordered and optimistic locking is a solution
Read projections processing events in order. A solution I used in the past was to to publish events on RabbitMQ and process them with Storm.
RabbitMQ has some guarantees about ordering and Storm has some processing affinity features. For Storm, (as far as I remember) allows you to specify that for a given ID (for example an Aggregate ID) the same handler would be used, hence the events are processed in the same order as received from RabbitMQ.
The article on MSDN https://msdn.microsoft.com/en-us/library/jj591559.aspx states "Stored events should be immutable and are always read in the order in which they were saved" under "Performance, Scalability, and consistency". This clearly means that appending events out of order is not tolerated. The same article also states multiple times that while events cannot be altered, corrective events can be made. This would imply again that events are processed in the order they are received to determine the current truth (state of of the aggregate). My conclusion is that we should fixed the messaging order problem before posting events to the event store.
I have a QuickFIX/J application running as acceptor. ResetOnLogon is N in the configuration.
When the initiator is logged on, since the seq nums are different the initiator app sends the messages and I see those messages in the FIX log file. The first one of those message is passed to the application layer but the others are not, all are discarded.
What can be the reason that the messages are received but not passed to the application level?
The most likely reason for this is that the messages contain the PossDupFlag <43> with a 'Y' value, and a MsgSeqNum <34> that is infact recognized as a dupe by the engine. In that case you won't receive these as application level messages.