I receive the error "Cannot time travel Delta table to version X" whereas I can see the version X when looking at the history on Azure Databricks

Question

I have a table in delta lake which has these tblproperties:

I'm trying to access a version which was there last month, the 322.

When I look at the history, I can see it:

But when I try to access it with such a command:

spark.read.format("delta").option("versionAsOf", 322).load(path)

I receive this error:

AnalysisException: Cannot time travel Delta table to version 322. Available versions: [330, 341].;

I can't understand the problem. I'm using Azure Databricks.

Are you able to read version 330 and 341. What commands you have used to write in to delta table? — Ali Hasan, Mar 11 '21 at 12:25
Yes, I'm able to read the versions 330 and 341. I've used the function "df.write.format("delta")..." to write a new data. — Nastasia, Mar 11 '21 at 13:11

score 0 · Accepted Answer · answered Mar 29 '21 at 07:17

I'm not sure to understand this bug. There's an open pull request in DeltaLake that might solve the problem: https://github.com/delta-io/delta/pull/627.

Till then, a person from Databricks gave me a workaround: set delta.checkpointRetentionDuration to X days. That will keep your checkpoints enough longer to have access to older versions.

Then, you must launch something like that in your delta table:

spark.sql(        f"""
        ALTER TABLE delta.`path`
            SET TBLPROPERTIES (
                delta.logRetentionDuration = 'interval X days',
                delta.deletedFileRetentionDuration = 'interval X days',
                delta.checkpointRetentionDuration = 'X days'
            )
        """
)

It will keep your versions until X days.

I receive the error "Cannot time travel Delta table to version X" whereas I can see the version X when looking at the history on Azure Databricks

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