I have access to table created by someone else which is periodically updating in Databricks. Lets call this table as 'table 1'. I want to create another table after manipulating data from table 1. What are the steps to follow. Do I need to define a schema before creating the table. Do I need to specify the location at the time of creating new table
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In SQL Server , we can create index like this. How do we create the index after the table already exists? What is the syntax of create clusted index in bigquery?
CREATE INDEX abcd ON `abcd.xxx.xxx`(columnname )
In big query, we can create table like below. But how to create partition and cluster on an existing table?
CREATE TABLE rep_sales.orders_tmp PARTITION BY DATE(created_at) CLUSTER BY created_at AS SELECT * FROM rep_sales.orders
As #Sergey Geron mentioned in the comments, BigQuery doesn’t support indexes. For more information, please refer to this doc.
An existing table cannot be partitioned but you can create a new partitioned table and then load the data into it from the unpartitioned table.
As for clustering of tables, BigQuery supports changing an existing non-clustered table to a clustered table and vice versa. You can also update the set of clustered columns of a clustered table. This method of updating the clustering column set is useful for tables that use continuous streaming inserts because those tables cannot be easily swapped by other methods.
You can change the clustering specification in the following ways:
Call the tables.update or tables.patch API method.
Call the bq command-line tool's bq update command with the --clustering_fields flag.
Note: When a table is converted from non-clustered to clustered or the clustered column set is changed, automatic re-clustering only works from that time onward. For example, a non-clustered 1 PB table that is converted to a clustered table using tables.update still has 1 PB of non-clustered data. Automatic re-clustering only applies to any new data committed to the table after the update.
I want to create an empty Athena table over an S3 bucket which will hold rows from other Athena tables. After each day, the data in this table gets old for my use case and hence I have to drop it and create a new table and insert latest rows into it.This table will be filled with rows from other tables and has nothing to do with data in the S3 bucket it is being created in. I want to use this table to just insert rows into it from other Athena tables, so that I can use quicksight on the data.
Right now, when I Drop and Create the Athena table over the same S3 bucket, it shows all the previous rows that were inserted into it. So in essence, how do I delete these previously inserted rows and get a empty table each time?
Right now I do something like this:
DROP TABLE IF EXISTS athena-table
CREATE EXTERNAL TABLE IF NOT EXISTS athena-table LOCATION 'SAME_S3_BUCKET'
I am trying to drop all the partitions on an external table in a redshift cluster. I am unable to find an easy way to do it. I am currently doing this by running a dynamic query to select the dates from the table and concatenating it with the drop logic and taking the result set and running it separately like this
select 'ALTER TABLE procore_iad_ext.active_histories DROP PARTITION (values='''||rtrim(ltrim(values, '["'),'"]') ||''');' from svv_external_partitions
where tablename = 'xyz';
values looks like this ->["2009-03-10"]
Looking for a simpler direct solution. Thanks.
The easiest way to do this would be to drop the table itself. As long as you have the DDL to recreate the table and don't mind dropping all partitions, just DROP TABLE <schemaname>.<tablename>; then recreate the table. The new table will not have any partitions.
Please check out the Glue catalog. It provides a UI to easily delete the tables/partitions etc.
Does the "Create table as" function in SQL Data Warehouse create statistics in the background, or do they have to manually be created (as I would when I do a normal "Create table" statement?)
As of the current version, you always have to create column-level statistics on tables, irrespective of whether it was created with a normal CREATE TABLE or the CTAS CREATE TABLE AS... command. It's also good practice to create stats for columns used in JOINs, WHERE clauses, GROUP BY, ORDER BY and DISTINCT clauses.
Regarding tables created with CTAS, the database engine has a correct idea of how many rows are in the table as listed in sys.partitions, but not at the column-level statistics level. For tables created by CREATE TABLE this defaults to 1,000 rows. For the example below, the first table was created with a CTAS and has 208 rows, the second table with an ordinary CREATE TABLE and INSERT from the first table and also has 208 rows, but sys.partitions believes it to have 1,000 eg
Creating any column-level statistics manually will correct this number.
In summary, always manually create statistics against important columns irrespective of how the table was created.
I want to query a Dynamo DB table based on an attribute UpdateTime such that I get the records which are updated in the last 24 hours. But this attribute is not an index in the table. I understand that I need to make this column as an index. But I do not know how do I write a query expression for this.
I saw this question but the problem is I do not know the table name on which I want to query before runtime.
To find out the table names in your DynamoDB instance, you can use the "ListTables" API: http://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_ListTables.html.
Another way to view tables and their data is via the DynamoDB Console: http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ConsoleDynamoDB.html.
Once you know the table name, you can either create an index with the UpdateTime attribute as a key or scan the whole table to get the results you want. Keep in mind that scanning a table is a costly operation.
Alternatively you can create a DynamoDB Stream that captures all of the changes to your tables: http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html.