I have a column in Dynamo DB which is backed up in S3, and is something like this:
{"attributes":
{"m":{"isBirthday":{"s":"0"},
"party":{"m":{"cake":{"bOOL":false},"pepsi":{"bOOL":false},"chips":{"bOOL":false},"fries":{"bOOL":false},"puffs":{"bOOL":false}}},"gift":{"s":"yes"}}},
"createdDate":{"n":"1521772435189"},
"modifiedDate":{"n":"1521772435189"}}
I need to use this S3 file in Athena and run query on the items in this "attributes".
I have tried multiple options to map it and then retrieve the values. However it doesnot work.
Please someone let me know how do I map it to my athena table to run query on this.
Related
I have been working with AWS Athena for a while and need to do create a backup and version control of the views. I'm trying to build an automation for the backup to run daily and get all the views.
I tried to find a way to copy all the views created in Athena using boto3, but I couldn't find a way to do that. With Dbeaver I can see and export the views SQL script but from what I've seen only one at a time which not serve the goal.
I'm open for any way.
I try to find answer to my question in boto3 documentation and Dbeaver documentation. read thread on stack over flow and some google search did not took me so far.
Views and Tables are stored in the AWS Glue Data Catalog.
You can Query the AWS Glue Data Catalog - Amazon Athena to obtain information about tables, partitions, columns, etc.
However, if you want to obtain the DDL that was used to create the views, you will probably need to use SHOW CREATE TABLE [db_name.]table_name:
Analyzes an existing table named table_name to generate the query that created it.
Have you tried using get_query_results in boto3? get_query_results
I have a .sql file filled with Athena queries.
Is there a way I can tell Athena to run the sql queries saved in s3://my-bucket/path/to/queries.sql?
In MySQL can do something like this (based in SO answer), but curious if possible in Athena
mysql> source \home\user\Desktop\test.sql;
Is there a way I can tell Athena to run the sql queries saved in s3://my-bucket/path/to/queries.sql?
I think there is no direct way to tell Athena to run query stored in S3.
In MySQL can do something like this (based in SO answer), but curious if possible in Athena.
If you want to do it at all, then yes, you should be able to run the query using AWS CLI.
Your steps should be look like this.
Get the query from S3 using CLI and store in temp variable
Pass the query stored in a temp variable to Athena Query CLI
Hope this will help.
I am trying to insert some values in a customer table:
INSERT into customer
(c_custkey,c_name,c_address,c_city,c_nation,c_region,c_phone,c_mktsegment)
VALUES (123,'ddf','sfvvc','ccxx','dddd','dddss','sszzs','sssaaaa');
I am using the Amazon Redshift Query Editor for this. The query is getting triggered twice and I can see that in STL_QUERY and STV_RECENTS tables.
Can someone help me resolve this and why does it work this way?
We have a very large number of folders and files in S3, all under one particular folder, and we want to crawl for all the CSV files, and then query them from one table in Athena. The CSV files all have the same schema. The problem is that the crawler is generating a table for every file, instead of one table. Crawler configurations have a checkbox option to "Create a single schema for each S3 path" but this doesn't seem to do anything.
Is what I need possible? Thanks.
Glue crawlers claims to solve many problems, but in fact solves few. If you're slightly outside the scope of what they designed for you're out of luck. There might be a way to configure it to do what you want, but in my experience trying to make Glue crawlers do things that aren't perfectly aligned with it is not worth the effort.
It sounds like you have a good idea of what the schema of your data is. When that is the case Glue crawlers also provide very little value. You probably have a better idea of what the schema should look than Glue will ever be able to figure out.
I suggest that you manually create the table, and write a one off script that lists all the partition locations on S3 that you want to include in the table and generate ALTER TABLE ADD PARTITION … SQL, or Glue API calls to add those partitions to the table.
To keep the table up to date when new partition locations are added, have a look at this answer for guidance: https://stackoverflow.com/a/56439429/1109
One way to do what you want is to use just one of the tables created by the crawler as an example, and create a similar table manually (in AWS Glue->Tables->Add tables, or in Athena itself, with
CREATE EXTERNAL TABLE `tablename`(
`column1` string,
`column2` string, ...
using existing table as an example, you can see the query used to create that table in Athena when you go to Database -> select your data base from Glue Data Catalog, then click on 3 dots in front of the one "automatically created by crawler table" that you choose as an example, and click on "Generate Create table DDL" option. It will generate a big query for you, modify it as necessary (I believe you need to look at LOCATION and TBLPROPERTIES parts, mostly).
When you run this modified query in Athena, a new table will appear in Glue data catalog. But it will not have any information about your s3 files and partitions, and crawler most likely will not update metastore info for you. So you can in Athena run "MSCK REPAIR TABLE tablename;" query (it's not very efficient, but works for me), and it will add missing file information, in the Result tab you will see something like (in case you use partitions on s3, of course):
Partitions not in metastore: tablename:dt=2020-02-03 tablename:dt=2020-02-04
Repair: Added partition to metastore tablename:dt=2020-02-03
Repair: Added partition to metastore tablename:dt=2020-02-04
After that you should be able to run your Athena queries.
What I understand from the AWS Glue docs is a craweler will help crawl and discover new data. However, I noticed that once I crawled once, if new data goes into S3, the data is actually already discovered when I query the data catalog from Athena for example. So, can I say I do not need a crawler to crawl everytime new data is added, unless there are new schemas?
In fact, if I know the schema of the files, I can just manually create the table and do without a crawler, am I correct?
If data is partitioned by some keys (placed in sub-folders, like /data/year=2018/month=11/day=2) then you need a crawler to register newly added partitions (ie. /day=3) in Data Catalog to be able to query it via Athena.
However, if data is not partitined or comes into already registered partitions then there is no need to run a crawler.
Alternatively to runnig a crawler you can discover and register new partitions by running Athena command MSCK REPAIR TABLE <table> or registering them manually.
The easiest way to create a table in Data Catalog is running a crawler. But if you know schema and have patience to compose CREATE TABLE Athena query or fill all fields via AWS Glue console then you can go that way as well.
If you have the schema then you don't need to use the crawler and you might get better results (the crawler assumes partition columns are strings for example).
As Yuriy says, remember to run MSCK REPAIR TABLE or register new partitions manually.
MSCK can time out if you've added a lot of partitions. If it does, keep running it until it completes normally.