In my following S3 bucket I've gz file without a header that contains one column
In Athena editor, I run the following statement
CREATE EXTERNAL TABLE IF NOT EXISTS `access_file_o`.`Access_one` (
`ad_id` string,
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = ',',
'field.delim' = ','
) LOCATION 's3://ttt.pix/2022/01/01/00/rrrf.log.1-2022_01_01_00_00_06_316845229-i-06877974d15a00d7e.gz/'
TBLPROPERTIES ('has_encrypted_data'='false','compressionType'='gzip');
The file looks like that
111,
222,
222,
3333,
The table has been created but when I query this table
select * from "Access_one"
there are no rows, only columns name.
Please advice
The location should be folder and not file
This URI working well
s3://ttt.pix/2022/01/01/00/
While this one returns an empty table.
LOCATION 's3://ttt.pix/2022/01/01/00/rrrf.log.1-2022_01_01_00_00_06_316845229-i-06877974d15a00d7e.gz
Related
I've seen other questions saying their query returns no results. This is not what is happening with my query. The query itself is returning empty strings/results.
I have an 81.7MB JSON file in my input bucket (input-data/test_data). I've setup the datasource as JSON.
However, when I execute SELECT * FROM test_table; it shows (in green) that the data has been scanned, the query was successful and there are results, but not saved to the output bucket or displayed in the GUI.
I'm not sure what I've done wrong in the setup?
This is my table creation:
CREATE EXTERNAL TABLE IF NOT EXISTS `test_db`.`test_data` (
`tbl_timestamp` timestamp,
`colmn1` string,
`colmn2` string,
`colmn3` string
)
ROW FORMAT SERDE 'org.openx.data.jsonserde.JsonSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = '1'
) LOCATION 's3://input-data/test_data/'
TBLPROPERTIES ('has_encrypted_data'='false',
'skip.header.line.count'='1');
Resolved this issue. The labels of the table (e.g. the keys) need to be the same labels in the file itself. Simple really!
I am new to Athena, and would request for some help.
I have multiple csv files in the following format. Pls note all fields are in double quotes. And total file size is about 5GB. If possible, I would rather do this without the use of Glue. Unless there is a reason to spend $ on running the crawlers.
"emailusername.string()","emaildomain.string()","name.string()","details.string()"
"myname1","website1.com","fullname1","address1 n details"
"myname2","website2.com","fullname2","address2 n details"
The following code on Athena works perfectly:
CREATE EXTERNAL TABLE IF NOT EXISTS db1.tablea (
`emailusername` string,
`emaildomain` string,
`name` string,
`details` string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES ("separatorChar" = ",", "escapeChar" = "\\")
LOCATION 's3://projectzzzz2/0001_aaaa_delme/'
TBLPROPERTIES ('has_encrypted_data'='false');
However I am neither able to cluster, nor use partitioning. The following code runs successfully. Post that I am also able to Load Partitions successfully. But no data is returned!
CREATE EXTERNAL TABLE IF NOT EXISTS db1.tablea (
`name` string,
`details` string
)
PARTITIONED BY (emaildomain string, emailusername string)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES ("separatorChar" = ",", "escapeChar" = "\\")
LOCATION 's3://projectzzzz2/0001_aaaa_delme/'
TBLPROPERTIES ('has_encrypted_data'='false');
MSCK REPAIR TABLE tablea;
SELECT * FROM "db1"."tablea";
Result: Zero records returned
If your intention is to create partitions on emaildomain, emailusername
You don’t need to have fields called emaildomain, emailusername in the table. However, you need to have 2 directories as domain1/user1 under your s3 location.
e.g. s3://projectzzzz2/0001_aaaa_delme/domain1/user1
make sure
copy your file to s3://projectzzzz2/0001_aaaa_delme ( not to the location s3://projectzzzz2/0001_aaaa_delme/domain1/user1)
then you can issue
ALTER TABLE tablea ADD PARTITION (emaildomain ='domain1', emailusername= 'user1') location ‘s3://projectzzzz2/0001_aaaa_delme/domain1/user1' ;
If you query the table tablea you will see new fields called emaildomain and emailusername been added automatically
As of my knowledge, whenever you add a new user or new email domain then you need to copy your file into the new folder and need to issue the ‘Alter table’ statement accordingly.
Getting timeout error for a full text query in Athena like this...
SELECT count(textbody) FROM "email"."some_table" where textbody like '% some text to seach%'
Is there any way to optimize it?
Update:
The create table statement:
CREATE EXTERNAL TABLE `email`.`email5_newsletters_04032019`(
`nesletterid` string,
`name` string,
`format` string,
`subject` string,
`textbody` string,
`htmlbody` string,
`createdate` string,
`active` string,
`archive` string,
`ownerid` string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES (
'serialization.format' = ',',
'field.delim' = ',',
'ESCAPED BY' = '\\'
) LOCATION 's3://some_bucket/email_backup_updated/email5/'
TBLPROPERTIES ('has_encrypted_data'='false');
And S3 bucket contents:
# aws s3 ls s3://xxx/email_backup_updated/email5/ --human
2020-08-22 15:34:44 2.2 GiB email_newsletters_04032019_updated.csv.gz
There are 11 million records in this file. The file can be imported within 30 minutes in Redshift and everything works OK in redshift. I will prefer to use Athena!
CSV is not a format that integrates very well with the presto engine, as queries need to read the full row to reach a single column. A way to optimize usage of athena, which will also save you plenty of storage costs, is to switch to a columnar storage format, like parquet or orc, and you can actually do it with a query:
CREATE TABLE `email`.`email5_newsletters_04032019_orc`
WITH (
external_location = 's3://my_orc_table/',
format = 'ORC')
AS SELECT *
FROM `email`.`email5_newsletters_04032019`;
Then rerun your query above on the new table:
SELECT count(textbody) FROM "email"."email5_newsletters_04032019_orc" where textbody like '% some text to seach%'
I have created a table in AWS Athena like this:
CREATE EXTERNAL TABLE IF NOT EXISTS default.test_line_breaks (
col1 string,
col2 string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES (
'separatorChar' = ',',
'quoteChar' = '\"',
'escapeChar' = '\\'
)
STORED AS TEXTFILE
LOCATION 's3://bucket/test/'
In the bucket I put a simple CSV file with the following context:
rec1 col1,rec2 col2
rec2 col1,"rec2, col2"
rec3 col1,"rec3
col2"
When I run data preview request SELECT * FROM "default"."test_line_breaks" limit 10; then Athena returns the following response:
How should I set ROW FORMAT to properly handle line breaks within the field values? So that rec3\ncol2 appears in col2.
The problem here is that the OpenCSV Serializer-Deserializer
Does not support embedded line breaks in CSV files.
See this documentation from AWS.
However, it might be possible to use RegexSerDe. Just remember that this Deserializer will take "Java Flavored" Regex. So be sure to use an online Regex tool that supports that syntax in your debugging.
Edit: Still working on the syntax for dealing with the embedded line feed \n. However, here is a sample that handles two columns with optional quotes. The following regex "*([^"]*)"*,"*([^"]*)"* worked on your line with the embedded return carriage. However, I think the Presto Engine is only feeding it rec3 col1,"rec3. I continue working on it.
CREATE EXTERNAL TABLE IF NOT EXISTS default.test_line_breaks (
col1 string,
col2 string
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe'
WITH SERDEPROPERTIES (
"input.regex" = '"*([^"]*)"*,"*([^"]*)"*'
)
STORED AS TEXTFILE
LOCATION 's3://.../47936191';
Hi Currently I have created a table schema in AWS Athena as follow
CREATE EXTERNAL TABLE IF NOT EXISTS axlargetable.AEGIntJnlActivityLogStaging (
`clientcomputername` string,
`intjnltblrecid` bigint,
`processingstate` string,
`sessionid` int,
`sessionlogindatetime` string,
`sessionlogindatetimetzid` bigint,
`recidoriginal` bigint,
`modifieddatetime` string,
`modifiedby` string,
`createddatetime` string,
`createdby` string,
`dataareaid` string,
`recversion` int,
`partition` bigint,
`recid` bigint
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES (
'separatorChar' = ',',
'quoteChar' = '\"',
'escapeChar' = '\\'
)
LOCATION 's3://ax-large-table/AEGIntJnlActivityLogStaging/'
TBLPROPERTIES ('has_encrypted_data'='false');
But one of the filed (processingstate) value contain comma as "Europe, Middle East, & Africa" which displace columns order.
So what would be the best way to read this file. Thanks
When I removed this part
WITH SERDEPROPERTIES (
'separatorChar' = ',',
'quoteChar' = '\"',
'escapeChar' = '\\'
)
I was able to read quoted text with commas in it
As workaround - look at aws glue project.
Instead of creating table via CREATE EXTERNAL TABLE:
invoke get-table for your table
Then make json for create-table
Merge the following StorageDescriptor part:
{
"StorageDescriptor": {
"SerdeInfo": {
"SerializationLibrary": "org.apache.hadoop.hive.serde2.OpenCSVSerde"
...
}
...
}
perform create via aws cli. You will get this table in aws glue and athena be able to select correct columns.
Notes
If your table already defined OpenCSVSerde - they may be fixed this issue and you can simple recreate this table.
I do not have much knoledge about athena, but in aws glue you can delete or create table without any data loss
Before adding this table via create-table you have to check first how glue or/and athena hadles table duplicates
This is a common messy CSV file situation where certain values contain commas. The solution in Athena for this is to use SERDEPROPERTIES as described in the AWS doc https://docs.aws.amazon.com/athena/latest/ug/csv-serde.html [the url may change so just search for 'OpenCSVSerDe for Processing']
Following is a basic create table example provided. Based on your data you would have to ensure that the data type is specified correctly (eg string)
CREATE EXTERNAL TABLE test1 (
f1 string,
s2 string)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES ("separatorChar" = ",", "escapeChar" = "\")
LOCATION 's3://user-test-region/dataset/test1/'