Forum Discussion
The database was evicted, AdomdErrorResponseException
hello js15
Give it a try
import sempy.fabric as fabric
df = fabric.read_table(
dataset="your_dataset_name",
table="your_large_table",
mode="onelake",
onelake_import_method="spark"
)Fabric’s `read_table` function supports a parameter called `mode` that lets you choose the data retrieval method. By switching the mode from the default `"xmla"` to `"onelake"` and specifying an appropriate import method (such as `"spark"`), you offload the heavy lifting to the Spark runtime rather than the XMLA engine. This approach can be particularly useful for large tables because it is designed to scale with distributed resources
if this helps please give kudos and accept the answer
hello js15
Give it a try
import sempy.fabric as fabric
df = fabric.read_table(
dataset="your_dataset_name",
table="your_large_table",
mode="onelake",
onelake_import_method="spark"
)
Fabric’s `read_table` function supports a parameter called `mode` that lets you choose the data retrieval method. By switching the mode from the default `"xmla"` to `"onelake"` and specifying an appropriate import method (such as `"spark"`), you offload the heavy lifting to the Spark runtime rather than the XMLA engine. This approach can be particularly useful for large tables because it is designed to scale with distributed resources
if this helps please give kudos and accept the answer