Why Does My Hive COUNT(*) Query Return Different Row Counts Depending on the WHERE Clause?

*Hive COUNT() query results vary depending on the WHERE clause**

When using Hive tables, you may encounter unexpected behavior when counting rows with or without null values. This difference can be explained by query statistics.

If Hive detects the presence of query statistics in a table, it may use this information to optimize query performance. When you execute a query without a WHERE clause, for example:

<code class="language-sql">SELECT COUNT(*) AS c FROM mytable</code>

Hive may use these statistics to estimate the number of rows in a table without actually reading the data. If the statistics are not up to date, this may lead to inaccurate results.

In contrast, when you add a WHERE clause with a non-null condition, for example:

<code class="language-sql">SELECT COUNT(*) AS c FROM mytable WHERE master_id IS NOT NULL</code>

Hive will be forced to read the data to filter out rows with empty master_id values. This precise count may be higher than estimated based on statistical information.

To avoid this behavior and ensure accurate row counts, you can disable statistics-based query optimization by setting:

<code class="language-sql">SET hive.compute.query.using.stats=false;</code>

Alternatively, you can explicitly analyze the table using the ANALYZE TABLE command to update statistics. You can also set:

<code class="language-sql">SET hive.stats.autogather=true;</code>

This will automatically collect statistics during INSERT OVERWRITE operations, keeping them up to date and reducing row count differences.

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