Amazon Redshift will no longer support the creation of new Python UDFs starting Patch 198. Existing Python UDFs will continue to function until June 30, 2026. For more information, see the [ blog post ](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/). 

# STV\$1TBL\$1TRANS
STV\$1TBL\$1TRANS

Use the STV\$1TBL\$1TRANS table to find out information about the transient database tables that are currently in memory.

Transient tables are typically temporary row sets that are used as intermediate results while a query runs. STV\$1TBL\$1TRANS differs from [STV\$1TBL\$1PERM](r_STV_TBL_PERM.md) in that STV\$1TBL\$1PERM contains information about permanent database tables.

STV\$1TBL\$1TRANS is visible only to superusers. For more information, see [Visibility of data in system tables and views](cm_chap_system-tables.md#c_visibility-of-data).

## Table columns
Table columns

[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/redshift/latest/dg/r_STV_TBL_TRANS.html)

## Sample queries
Sample queries

To view transient table information for a query with a query ID of 90, type the following command: 

```
select slice, id, rows, size, query_id, ref_cnt 
from stv_tbl_trans
where query_id = 90;
```

This query returns the transient table information for query 90, as shown in the following sample output: 

```
slice | id | rows | size | query_ | ref_ | from_     | prep_
      |    |      |      | id     | cnt  | suspended | swap
------+----+------+------+--------+------+-----------+-------
 1013 | 95 |    0 |    0 |     90 |    4 |         0 |   0
    7 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   10 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   17 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   14 | 96 |    0 |    0 |     90 |    4 |         0 |   0
    3 | 96 |    0 |    0 |     90 |    4 |         0 |   0
 1013 | 99 |    0 |    0 |     90 |    4 |         0 |   0
    9 | 96 |    0 |    0 |     90 |    4 |         0 |   0
    5 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   19 | 96 |    0 |    0 |     90 |    4 |         0 |   0
    2 | 96 |    0 |    0 |     90 |    4 |         0 |   0
 1013 | 98 |    0 |    0 |     90 |    4 |         0 |   0
   13 | 96 |    0 |    0 |     90 |    4 |         0 |   0  
    1 | 96 |    0 |    0 |     90 |    4 |         0 |   0
 1013 | 96 |    0 |    0 |     90 |    4 |         0 |   0
    6 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   11 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   15 | 96 |    0 |    0 |     90 |    4 |         0 |   0
   18 | 96 |    0 |    0 |     90 |    4 |         0 |   0
```

In this example, you can see that the query data involves tables 95, 96, and 98. Because zero bytes are allocated to this table, this query can run in memory.