How does MAXSIZE affect billing? I see that the default value is now 240TBs. What if I'm only using 10TB of space? Will I still be charged for the entire 240TB size?
No, it's a configuration change that allows your DW to grow to that size. You only get billed for actual usage, rounded up to the next TB.
Related
I am working on an application which receives very predictable, heavy traffic during working hours. Users typically interact with the app for about 40 minutes at a time. DynamoDB table A receives a steady stream of writes throughout user sessions and handles things without difficulty. We attempt to write a large amount of data to table B at the end of each session, however, and early in the day this can result in throttling. Our tables are billed on-demand (no, this is not something I am able to change), but the sudden spike in writes still causes throttling, which is expected.
The data being written to table A is both critical and time sensitive. The data going to table B is critical and must not be lost, but delays in data availability from table B on the order of a few hours is acceptable, but not ideal. So I'm looking for a way to say "please write this to the table ASAP, but only as long as it won't cause throttling". Provisioning for the expected capacity is not an option (don't ask). An SQS queue with a long message delay doesn't really fit the bill because (a) 15 minutes may not be long enough and (b) it doesn't meet the "ASAP" part of the story. I've considered pre-warming the table, but that's just cludgy.
So... you take all the expected ways to handle this that were designed and provided by AWS then say you can't use them. That... doesn't leave you much options.
You're pretty much left with designing some custom architecture. Throttling, provisioning, burst provisioning, on demand, and all are all part of the package for handling these kinds of bursts. If you can't use them, then you'll have to do something like write the entry as a json to an s3 bucket and have some cron event pick them up in an hour or something one a time and batch write them to the table.
You may want to take a look at how your table is arranged. If you are having to make a lot of writes all at once (ie, because you have to duplicate data through multiple PK/SK combinations in order to be able to recall it with a single query) then an RDS may be better suited for the task at hand. Dynamo is more for quick and snappy queries and not really for extended data logging or storage.
Here's the secret to DDB on-demand...
From the page you linked to
For new on-demand tables, you can immediately drive up to 4,000 write
request units or 12,000 read request units, or any linear combination
of the two. For an existing table that you switched to on-demand
capacity mode, the previous peak is half the previous provisioned
throughput for the table—or the settings for a newly created table
with on-demand capacity mode, whichever is higher. For more
information, see Initial throughput for on-demand capacity mode.
And the Inital throughput for on-demand capacity mode page says:
Initial Throughput for On-Demand Capacity Mode If you recently
switched an existing table to on-demand capacity mode for the first
time, or if you created a new table with on-demand capacity mode
enabled, the table has the following previous peak settings, even
though the table has not served traffic previously using on-demand
capacity mode:
Newly created table with on-demand capacity mode: The previous peak is
2,000 write request units or 6,000 read request units. You can drive
up to double the previous peak immediately, which enables newly
created on-demand tables to serve up to 4,000 write request units or
12,000 read request units, or any linear combination of the two.
Existing table switched to on-demand capacity mode: The previous peak
is half the maximum write capacity units and read capacity units
provisioned since the table was created, or the settings for a newly
created table with on-demand capacity mode, whichever is higher. In
other words, your table will deliver at least as much throughput as it
did prior to switching to on-demand capacity mode.
The key thing to realize is that DDB on-demand "peaks" are never lowered..
So if you have a table that at some point peaked at 20K WCU, you can scale cleanly from 1-20K without throttling.
In other words, you shouldn't continue to see throttling in an app unless you hit a new peak.
You can also artificially set the peak by changing the table to provisioned at double the expected peak. Then when you convert it back to on-demand, you'll have a "peak" set for half the provisioned capacity.
Looking at this page: Power BI features comparison I see that a dataset can be 10gb and storage is limited to 100tb. Can I take this to mean there is a limit of 10,000 10gb apps?
Also is there a limit on the number of users? It implies no with the statement "Licensed by dedicated cloud compute and storage resources", but I wanted to be sure.
I assume I am paying for compute so the real limits are based on what compute resources I purchase? Are there any limits on this?
Thanks.
Yes you can have 10,000 10GB datasets, to use up the total volume of 100TB, however storage will also be used for Excel Workbooks, Dataflows storage, as well as Excel ranges pinned to a dashboard, and other uploaded images.
There is no limit on the total number of users, however there is a limit based on 'peak renders per hour', which means how often users interact with the report. PBI Premium does expect you you have a mix of frequent and infrequent users, so for Premium P1 nodes, the peak renders per hour is 1 to 2400. Anything over that, you may experience performance degradation on that node is for example you had 3500 renders of a report in an hour, but it will depend on the type of report, queries etc. You can scale up to quite a number of nodes if you need to, Power BI Premium Gen 2 does allow auto scale.
I am currently building a graph using AWS Neptune. Is there a way of determining or calculating the size of a filled database with AWS Neptune?
There is an answer already in this post, but posting one more with a bit more details, as the previous answer does not mention if the storage includes space used by replication, deleted data etc.
As #Morinaga already pointed out, Cloudwatch exposes the amount of bytes used by actual datapages under AWS/Neptune -> By Cluster -> VolumeBytesUsed. This shows the exact storage that you get charged for. Internally Neptune uses a distributed storage for the data, which includes multiple copies, some additional storage for metadata etc. None of that info impacts how you get billed, so they are not included in VolumeBytesUsed.
Neptune also supports copy-on-write, where you can create a cloned volume from another cluster. One thing to note with cloned volumes is that the new cluster only takes us space for pages that have diverged from the source. So when you plot the VolumeBytesUsed metric for a clone, you would see a much smaller number for the clone as long as the source cluster is still active and lying around. If you delete the source cluster, the space is then re-adjusted in the clones. Do make a note of this, to avoid any possible confusion later on.
Last thing to note is that Neptune, as of Sept 2020, does not do volume shrinking. The VolumeBytesUsed is pretty much a high watermark of how much data pages were used, and deleting a lot of data just clears the data in the data pages, it does not remove it from the volume. So if you create a cluster, add a bunch of data and them delete everything, your VolumeBytesUsed would still show the high watermark. When you insert new data, we would reuse the available data pages first, so you don't end up paying for new data pages.
AWS Cloud Watch can be used to figure out the exact size of your filled database.
Under Metrics you can select Neptune and search for the MetricName='VolumeBytesUsed'. This will show you the amount of data that has been uploaded to your database.
It really depends on how much data you store in vertex and edge properties. Taylor answer here explains more as storage capacity is dynamically allocated in Amazon Neptune.
I am working on Amazon DynamoDB audit table.
The read/write mode was set to "Provisioning". Now, the mode is changed to "On-Demand". I have an "Audit Table" (which captures the audit information like date and time of operation, user details, etc) associated with DynamoDB.
My questions on this are:
1) How is it impacting the data that gets created in the "Audit Table"?
2) Will the data be deleted automatically on timely bases?
3) If not, what is the maximum limit of data that a table (audit table in this case) can persist?
Please let me know if you need any more information from my side.
Waiting for your answers on my questions.
Thanks and regards,
Mahesh Bongale
Provisioning just means that the table is initializing with whatever read/write capacity you set, or OnDemand capacity if you set it to that mode (similar to an auto-scaling mode where it will always deliver the throughput needed by your application). More info: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.html
No, absolutely not, unless you specifically add code that will delete old data OR set a specific TTL on your data. More info: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html
There is no specific limit on the number of rows in a given table. It can be as much as you want. There are a few limits though on a few things, some can be lifted if you ask AWS, some can not: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Limits.html
For my application I am using free tier aws account I have given 5 read capacity and 5Write capacity(i can’t increase the capacity because they will charge if I increase) to the dynamo db here I am using scan operation. The api is loading in between 10 seconds to 20 seconds.
I have used parallel scan too but the api is loading same time. Is there any alternate service in aws.
click here to see the image
It is not a good idea to use a Scan on a NoSQL database.
DynamoDB is optimize for Query requests. The data will come back very quickly, guaranteed (within the allocated Capacity).
However, when using a Scan, the database must read each item from the database and each item consumes a Read Capacity unit. So, if you have a table with 1000 items, a Query on one item would consume one Unit, whereas a Scan would consume 1000 Units.
So, either increase the Capacity Units (and cost) or, best of all, use a Query rather than a Scan. Indexes can also help.
You might need to re-think how you store your data if you always need to do a Scan.