Improving Explain Text Readability - Teradata VantageCloud Lake

Lake - Database Reference

Deployment
VantageCloud
Edition
Lake
Product
Teradata VantageCloud Lake
Release Number
Published
February 2025
ft:locale
en-US
ft:lastEdition
2025-11-21
dita:mapPath
ohi1683672393549.ditamap
dita:ditavalPath
pny1626732985837.ditaval
dita:id
ohi1683672393549

To combine multiple ExplainText doc rows with the same query ID into one easily readable document, perform a SELECT request on the QryLogExplainDocV view.

Example

sel queryid,explaintextdoc from qrylogexplaindocv where queryid=307188741814475132;

The result looks like the following partial output:

 *** Query completed. One row found. 2 columns returned.
 *** Total elapsed time was 1 second.

QueryID  ExplainTextDoc

  307188741814475132    1) First, we lock Test_DB.b12 for read on a reserved rowHash to      prevent global deadlock.    2) Next, we lock Test_DB.b3 for read on a reserved rowHash to      prevent global deadlock.    3) We lock Test_DB.b12 for read, and we lock Test_DB.b3 for      read.    4) We do an all-AMPs RETRIEVE step from Test_DB.b3 by way of an all-rows scan with a condition of ("NOT (Test_DB.b3.c2 IS NULL)") into Spool 2 (all_amps), which is redistributed by the hash code of (Test_DB.b3.c2) to all AMPs.  Then we do a SORT to order      Spool 2 by row hash.  The size of Spool 2 is estimated with low confidence to be 4 rows (68 bytes).  The estimated time for this step is 0.03 seconds.    5) We execute the following steps in parallel.... 
Export the result set to a file. On the monitor, lines may truncate.

The memory allocated for the input is 32 MB.