Loading Snowflake tables
To mount a Snowflake database into the sgr engine using
SqlAlchemyFdw,
run:
$ sgr mount snowflake local_schema -o@- <<EOF
{
"username": "username",
"secret": {
"secret_type": "password",
"password": "password"
},
"account": "acc-id.west-europe.azure",
"database": "SNOWFLAKE_SAMPLE_DATA",
"schema": "TPCH_SF100",
"envvars": {"HTTPS_PROXY": "http://proxy.company.com"}
}
EOF
This will mount a remote Snowflake schema TPCH_SF100 from the
SNOWFLAKE_SAMPLE_DATA database into a local schema local_schema on the local
sgr engine.
Alternatively, you can mount specific tables:
$ sgr mount snowflake test_snowflake_subquery -o@- <<EOF
{
"username": "username",
"secret": {
"secret_type": "private_key",
"private_key": "MIIEvQIBAD..."
},
"account": "acc-id.west-europe.azure",
"database": "SNOWFLAKE_SAMPLE_DATA",
"tables": {
"balances": {
"schema": {
"n_nation": "varchar",
"segment": "varchar",
"avg_balance": "numeric"
},
"options": {
"subquery": "SELECT n_nation AS nation, c_mktsegment AS segment, AVG(c_acctbal) AS avg_balance FROM TPCH_SF100.customer c JOIN TPCH_SF100.nation n ON c_nationkey = n_nationkey"
}
}
}
}
EOF
To snapshot the table, making it part of an actual Splitgraph image, use the
sgr import command.
