# Investigating Memory Usage Discrepancies

When there is a large discrepancy between the sum of memory usage from `information_schema.TABLE_STATISTICS` vs what is reported in `alloc_table_memory`, review the internal table statistics via [`information_schema.INTERNAL_TABLE_STATISTICS`](https://docs.singlestore.com/db/v9.1/reference/information-schema-reference/query-performance-workload-management-and-statistics/table-statistics-and-internal-table-statistics.md) to see where the rest of memory is being held. For example:

```sql
SHOW STATUS EXTENDED LIKE '%Alloc_table_memory%';

```

```output

+--------------------+-----------------------+
| Variable_name      | Value                 |
+--------------------+-----------------------+
| Alloc_table_memory | 39389.780 (+0.125) MB |
+--------------------+-----------------------+
1 row in set (0.00 sec)
```

Compare that information with the results of:

```sql
SELECT SUM(memory_use)/1024/1024/1024 MEM_GB FROM information_schema.table_statistics 
  WHERE 1=1 AND host = 'leaf-1.example.com';

```

```output

+----------------+
| MEM_GB         |
+----------------+
| 2.392731554806 |
+----------------+
1 row in set (0.76 sec)
```

The alloc variable is showing 39 GB while table statistics shows just 2.39 GB. 

The next step would be to examine the `md_`\<table> information in `information_schema.INTERNAL_TABLE_STATISTICS` for outliers to see where the rest of the memory is being held. For example, extremely large unlimited storage databases can result in `md_columnar_blobs` storing large amounts of data for each node.

***

Modified at: August 8, 2025

Source: [/db/v9.1/reference/troubleshooting-reference/identifying-and-reducing-memory-usage/investigating-memory-usage-discrepancies/](https://docs.singlestore.com/db/v9.1/reference/troubleshooting-reference/identifying-and-reducing-memory-usage/investigating-memory-usage-discrepancies/)

(An index of the documentation is available at /llms.txt)