Why has Datastream throughput dropped to near zero after the backfill completed? - google-datastream

I have a stream running from MySQL to BigQuery. The backfill completely perfectly but when it was finished the ongoing stream is just not picking up changes to almost all of the tables. Just a few here and there, almost nothing is going though. The stream is running and I have no errors however. Any tips on how I can troubleshoot this in more detail?


commitOffsetsInFinalize() and checkmarks in Apache Beam

I am working on a Beam application that uses KafkaIO as an input
KafkaIO.<Long, GenericRecord>read()
I am trying to understand how exactly the commitOffsetsInFinalize() works.
How can the streaming job be finalized?
The last step in the pipeline is a custom DoFn that writes the messages to DynamoDb. Is there any way to manually call some finalize() method there, so that the offsets are committed after each successful execution of the DoFn?
Also I am having hard time understanding whats the relation between the checkpoints and the finalization ? If no checkpoint is enabled on the pipeline, will I still be able to finalize and get the commitOffsetsInFinalize() to work?
p.s The way the pipeline is right now, even with the commitOffsetsInFinalize() each message that is read, regardless whether there is a failure downstream is being committed, hence causing a data lose.
Thank you!
The finalize here is referring to the finalization of the checkpoint, in other words when the data has been durably committed into Beam's runtime state (such that worker failures/reassignment will be retried without having to read this message from Kafka again). This does not mean that the data in question has made its way the rest of the way through the pipeline.

Write flink stream to relational database

I am working on a flink project which write stream to a relational database.
In the current solution, we wrote a custom sink function which open transaction, execute SQL insert statement and close transaction. It works well until the the data volume increases and we started getting connection timeout issues. We tried a few connection pool configuration adjustment, it does not help much.
We are thinking of trying "batch-insert", so to decrease the number of "writes" to the database. We come across a few classes which do almost what we want: JDBCOutputFormat, JDBCSinkFunction. With JDBCOutputFormat, we can configure the batch size.
We would also like to force a "batch-insert" every 1 minutes if the number of records does not exceed the "batch-size". How would you normally deal with these kinds of problems? My first thoughts is to extend JDBCOutputFormat to use scheduled tasks to force flush every 1 minute, but it was not obvious how it could be done.
Do we have to write our own sink all together?
JDBCSinkFunction does a flush and batch execute each time Flink checkpoints. So long as you are doing checkpointing, the batches won't be any longer than the checkpointing interval.
However, having read this mailing list thread, I see that JDBCSinkFunction does not support exactly-once output.

Flink EMR Program failing

I have, what I would consider, a fairly simple Flink program. Sourced from a Kafka stream, filter's applied, process function applied, flat map applied, and sent to a Redis sink. Running this locally in a stand alone environment on my dev box, there is no problem. I am trying to push this into production on AWS EMR, I followed the guide for running a Flink program on EMR. After my first test, I had a GC overhead limit exceeded error, so I made adjustments to reduce the amount of data stored. My next try the program ran for much longer, but eventually failed, not giving any indication of a type of error like it had previously.
I am unsure how to go about debugging problems that I suspect may be a side effect of running on EMR. Most of the monitoring metrics in the EMR console are useless as far as I can tell. If it matters, I am running the program as a Step in EMR, the guide i followed is here http://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-flink.html. This program is also suppose to be an always up solution, basically it will constantly be reading from the Kafka Stream and processing the data(If that matters at all, not sure if there is a different configuration I should be using for an always up solution)
I'll be happy to provide any information needed to help me getting this into production.
Thank you

Is relational database appropriate for soft real-time system?

I'm working on a real-time video analysis system which processes the video stream frame by frame. At each frame it can generate several events which should be recorded and some delivered to another system via network. The system is soft real-time, i.e. message latencies higher than 25ms are highly undesirable, but not fatal.
Are relational databases (specifically, MySQL and Postgres) appropriate as the datastore for such system?
Can I expect the DB to work well when it is installed on its own server and has ~50 25fps streams of single-row SQL inserts coming in over the network?
EDIT: I think in general performance would not be a problem, but I worry about the latency variance. If it will occasionally delay for 1000 ms, that would be very bad.
Oh, and the system runs 24/7 so the DB could grow arbitrarily big. Does that degrade the insert latency?
I wouldn't worry too much about performance when choosing a relational database over another type of datastore, choose the solution that best meets your requirements for accessing that data later. However, if you do choose not only a RDBMS but one over the network then you might want to consider buffering events to a local disk briefly on their way over to the DB. Use a separate thread or process or something to push events into the DB to keep the realtime system unaffected.
Biggest problems are how unpredictable the latency will be and how it never goes down, always up. But modern hardware to the rescue, specify a machine with enough cpu cores. You can count on at least two, getting four is easy. So you can spin up a thread and dedicate one core to the dbase updates, isolating it from your soft real-time code. Now you don't care about the variability in the delays, at least as long as the dbase updates don't take so long that you generate data faster than it can consume.
Setup a dbase server and load it up with fake data, double the amount you think it ever needs to store. Test continuously while you develop, add the instrumenting code you need to measure how it is doing at an early stage in the project.
As I've written, if you queue the rows that need to be saved and save them in an async way (so not to stop the "main" thread) there shouldn't be any problem... BUT!!!
You want to save them in a DB... So someone else will read the rows AT THE SAME TIME they are being written. Sadly it's normally quite difficult to tell to a DB "this work is very high priority, everything else can be stalled but not this". So if someone does:
WAITFOR DELAY '01:00:00'
(I'm using T-Sql here... But I think it's quite clear. Ask for the COUNT(*) of the table, so that there is a lock on the table and then WAITFOR an hour)
then the writes could be stalled and go in timeout. In general if you configure everyone but the app to be able only to do reads, these problems shouldn't be present.

Prioritizing I/O for a specific query request in SQL server

Sorry for the long introduction but before I can ask my question, I think giving the background would help understanding our problem much better.
We are using sql server 2008 for our web services as the backend and from time to time it takes too much time for responding back for the requests that supposed to run really fast, like taking more than 20 seconds for a select request that queries a table that has only 22 rows. We went through many potential areas that could cause the issue from indexes to stored procedures, triggers etc, and tried to optimize whatever we can like removing indexes that are not read but write frequently or adding NOLOCK for our select queries to reduce the locking of the tables (we are OK with dirty reads).
We also had our DBA's reviewed the server and benchmarked the components to see any bottlenecks in CPU, memory or disk subsystem, and found out that hardware-wise we are OK as well. And since the pikes are occurring occasionally, it is really hard to reproduce the error on production or development because most of the time when we rerun the same query it yields response times that we are expecting, which are short, not the one that has been experienced earlier.
Having said that, I almost have been suspicious about I/O although it is not seem to be a bottleneck. But I think I was just be able to reproduce the error after running an index fragmentation report for a specific table on the server, which immediately caused pikes in requests not only run against that table but also in other requests that query other tables. And since the DB, and the server, is shared with other applications we use and also from time to time queries can be run on the server and database that take long time is a common scenario for us, my suspicion regarding occasional I/O bottleneck is, I believe, becoming a fact.
Therefore I want to find out a way that would prioritize requests that are coming from web services which will be processed even if there are other resource sensitive queries being run. I have been looking for some kind of prioritization I described above since very beginning of the resolution process and found out that SQL Server 2008 has a feature called 'Resource Governor' that allows prioritization of the requests.
However, since I am not an expert on Resource Governor nor a DBA, I would like to ask other people's experience who may have used or is using Resource Governor, as well as whether I can prioritize I/O for a specific login or a specific stored procedure (For example, if one I/O intensive process is being run at the time we receive a web service request, can SQL server stops, or slows down, I/O activity for that process and give a priority to the request we just received?).
Thank you for anyone that spends time on reading or helping out in advance.
Some Hardware Details:
CPU: 2x Quad Core AMD Opteron 8354
Memory: 64GB
Disk Subsystem: Compaq EVA8100 series (I am not sure but it should be RAID 0+1 accross 8 HP HSV210 SCSI drives)
PS:And I can almost 100 percent sure that application servers are not causing the error and there is no bottleneck we can identify there.
Update 1:
I'll try to answer as much as I can for the following questions that gbn asked below. Please let me know if you are looking something else.
1) What kind of index and statistics maintenance do you have please?
We have a weekly running job that defrags indexes every Friday. In addition to that, Auto Create Statistics and Auto Update Statistics are enabled. And the spikes are occurring in other times than the fragmentation job as well.
2) What kind of write data volumes do you have?
Hard to answer.In addition to our web services, there is a front end application that accesses the same database and periodically resource intensive queries needs to be run to my knowledge, however, I don't know how to get, let's say weekly or daily, write amount to DB.
3) Have you profiled Recompilation and statistics update events?
Sorry for not be able to figure out this one. I didn't understand what you are asking about by this question. Can you provide more information for this question, if possible?
first thought is that statistics are being updated because of the data change threshold is reached causing execution plans to be rebuilt.
What kind of index and statistics maintenance do you have please? Note: index maintenance updates index stats, not column stats: you may need separate stats updates.
What kind of write data volumes do you have?
Have you profiled Recompilation and statistics update events?
In response to question 3) of your Update to the original question, take a look at the following reference on SQL Server Pedia. It provides an explanation of what query recompiles are and also goes on to explain how you can monitor for these events. What I believe gbn is asking (feel free to correct me sir :-) ) is are you seeing recompile events prior to the slow execution of the troublesome query. You can look for this occurring by using the SQL Server Profiler.
Reasons for Recompiling a Query Execution Plan