I have a query that I want to execute daily that's to be partitioned by the date it's executed. The results of this query should be appended to a the same table.
My idea was ideally having something similar to the CREATE TABLE IF NOT EXISTS command for adding data by a new partition every day to the existing table if the partition doesn't already exist, but I can't figure out how I'd be able to integrate this in my query.
My query:
CREATE TABLE IF NOT EXISTS db_name.table_name
WITH (
external_location = 's3://my-query-results-location/',
format = 'PARQUET',
parquet_compression = 'SNAPPY',
partitioned_by = ARRAY['date_executed'])
AS
SELECT
{columns_that_I_am_selecting_here_including_'date_executed'}
What this does is create a new table for the first day it's executed but nothing happens for subsequent days, I'm assuming because of the CREATE TABLE IF NOT EXISTS validating that the table already exists and not proceeding with the logic.
Is there a way to modify my query to create a table for the first day executed and append the results by a new partition for each subsequent day?
I'm quite sure ALTER TABLE table_name ADD [IF NOT EXISTS] PARTITION would not apply to my use case here as I'm running a CTAS query.
You can simply use INSERT INTO existing_table SELECT....
Presumably your table is already partitioned, so include that partition column in the SELECT and Amazon Athena will automatically put the data in the correct directory.
For example, you might include hte column like this: SELECT ... CURRENT_DATE as date_executed
See: INSERT INTO - Amazon Athena
Related
I have a table in AWS Athena which contains 2 records. Is there a SQL query using which a new column can be inserted in to the table?
You can find more information about adding columns to table in Athena documentation
Or you can use CTAS
For example, you have a table with
CREATE EXTERNAL TABLE sample_test(
id string)
LOCATION
's3://bucket/path'
and you can create another table from sample_test with the query
CREATE TABLE new_test
AS
SELECT *, 'new' AS new_col FROM sample_test
You can use any available query after AS
This is mainly for future readers like me, who was struggling to get this working for Hive table with AVRO data and if you don't want to create new table i.e updating schema of the existing table. It works for csv using 'add columns', but not for Hive + AVRO. For Hive + AVRO, to append columns at the end, before partition columns, the solution is available at this link. However, there are couple of things to note that, we need to pass full schema to the literal attribute and not just the changes; and (not sure why but) we had to alter hive table for all 3 things in the same order - 1. add columns using add columns 2. set tblproperties and 3. set serdeproperties. Hopefully it helps someone.
I want to create a Partitioned Table in Hive. I know to create a table structure first with the help of "Create table ... Partitioned by" command and then insert the data into the table using "Insert Into Table" command
But what I am trying to do is to combine these two commands into a single query like below but it is throwing errors.
CREATE TABLE test_extract AS
SELECT
*
FROM master_extract
PARTITION BY (year string
,month string)
;
Both Year and Month are two separate columns in the master_extract table.
Is there any way to achieve something like this ?
No, this is not possible, because Create Table As Select (CTAS) has restrictions:
The target table cannot be a partitioned table.
The target table cannot be an external table.
The target table cannot be a list bucketing table.
You can create table separately and then insert overwrite it.
There has been some development since this question was originally asked and answered. As per hive documentation: Starting with Hive 3.2.0, CTAS statements can define a partitioning specification for the target table (HIVE-20241).
You can also see the related ticket here. It has been resolved back in July 2018.
Therefore if your hive is of 3.2.0 or higher, then you can simply do
CREATE TABLE test_extract PARTITIONED BY (year string, month string) AS
SELECT
col1,
col2,
year,
month
FROM master_extract
I'm processing a big hive's table (more than 500 billion records).
The processing is too slow and I would like to make it faster.
I think that by adding partitions, the process could be more efficient.
Can anybody tell me how I can do that?
Note that my table already exists.
My table :
create table T(
nom string,
prenom string,
...
date string)
Partitioning on date field.
Thx
SET hive.exec.dynamic.partition = true;
SET hive.exec.dynamic.partition.mode = nonstrict;
INSERT OVERWRITE TABLE table_name PARTITION(Date) select date from table_name;
Note :
In the insert statement for a partitioned table make sure that you are specifying the partition columns at the last in select clause.
You have to restructure the table. Here are the steps:
Make sure no other process is writing to the table.
Create new external table using partitioning
Insert into new table by selecting from the old table
Drop the new table (external), only table will be dropped but data will be there
Drop the old table
Create the table with original name by pointing to the location under step 2
You can run repair command to fix all the metadata.
Alternative 4, 5, 6 and 7
Create the table with original name by running show create table on new table and replace with original table name
Run LOAD DATA INPATH command to move files under partitions to new partitions of new table
Drop the external table created
Both the approaches will achieve restructuring with one insert/map reduce job.
I've got a table with two weeks worth of entries, and I would like to copy those entries into a table partitioned by date (creating it if it does not exist).
I'm writing a luigi task to do this, and I would love for it to be independent of the table schema--i.e. I wouldn't have to specify column names and types, and it would CREATE TABLE IF NOT EXISTS when necessary.
I was hoping I could use:
CREATE TABLE IF NOT EXISTS test_part
COMMENT 'This is a test table to see if partitioning works in this case'
PARTITIONED BY (event_date string)
AS select *, '2014-12-15' from source_db.source_table
where event_at <'2014-12-16' and event_at >='2014-12-15';
But this of course fails with: FAILED: SemanticException [Error 10068]: CREATE-TABLE-AS-SELECT does not support partitioning in the target table
I tried again with "like" with basically the same results. Is there a way to do this that I am missing? It doesn't have to be atomic. Multiple sequential commands are fine.
You do not do a create table as.
You create a table first using describe source_table and then you make an insert into table partition (event_date string)
2 steps it works better.
I have a sql statement to insert data into a table for archiving, but I need a merge statement to run on a monthyl basis to update the new table(2) with any data that changed in the old table(1) that should now be moved into archive.
Part of the issue is to remove the moved data from the old table. My insert is not doing that, but I need to have it to where the saved data is purged from the original table.
Is there a single sql statement that will move data out of one table into another in this way? Or does it need to be a two step operation?
the initial statement moved data depending on age and a few other relative factors.
insert is:
INSERT /*+ append */
INTO tab1
SELECT *
FROM tab2
WHERE (Postingdate < TO_DATE ('2001/07/01', 'yyyy/mm/dd')
OR jobname IS NULL)
AND STATUS <> '45';
All help appreciated...
The merge statement will let you do this in one statement by adding a delete statement in the update clause. See Oracle Documentation on Merge.
I think you should try this with a partition table. My idea is to create table which have range partition on date:
create table(id number primary key,name varchar,J_date date )
partition by range(J_date)(PARTITION one_mnth VALUES LESS THAN(sysdate-30)),
partition by range(J_date)(PARTITION one_mnth VALUES LESS THAN(maxvalue)));
then move that partition in to another table and and truncate that partition