Get row counts and distinct row counts for every table in a Snowflake database? - sql

Question

I am trying to create a data quality dashboard, showing every table in my Snowflake database, the row count, the distinct row count, and the number of duplicates. The table I want should look like this:
table_name | row_count | distinct_row_count | duplicates
————————————————————————————————————————————————————————
table_a | 1,372 | 1,370 | 2
table_b | 4,735 | 4,735 | 0
I've been able to get the table name and row count using information_schema.tables. I'm trying to figure out how to get distinct counts for all of these tables. The primary key column for every table is different. On some tables it will be a user_id, on others a session_id, etc.
I've looked through the snowflake documentation for built in functions that could help. I've explored the information/usage schemas, etc. I'm not sure if a stored procedure would help here (I haven't used a lot of those).
In python or another language, I'd loop through every table and calculate what I need. Is there a way to do this in SQL?

Answer 1

create or replace TABLE DEMO_DB.PUBLIC.SNOWBALL (
TABLE_NAME VARCHAR(314),
TOTAL_ROWS NUMBER(18,0),
TABLE_LAST_ALTERED TIMESTAMP_LTZ(9),
TABLE_CREATED TIMESTAMP_LTZ(9),
TABLE_BYTES NUMBER(18,0),
COL_NAME ARRAY,
COL_DATA_TYPE ARRAY,
COL_HLL ARRAY,
COL_NULL_CNT ARRAY,
COL_MIN ARRAY,
COL_MAX ARRAY,
COL_TOP ARRAY,
COL_AVG ARRAY,
COL_MODE ARRAY,
COL_STDDEV ARRAY,
COL_VAR_POP ARRAY,
COL_AVG_LENGTH ARRAY,
STATS_RUN_DATE_TIME TIMESTAMP_LTZ(9)
);
create or replace view SNOWBALL_COLUMNS as
select
concat_ws('.', table_catalog, table_schema, table_name) as full_table_name,
*
from (
select * from demo_db.information_schema.columns
union
select * from snowflake_sample_data.information_schema.columns
union
select * from util_db.information_schema.columns
);
create or replace view SNOWBALL_TABLES as
select
concat_ws('.', table_catalog, table_schema, table_name) as full_table_name,
*
from (
select * from demo_db.information_schema.tables
union
select * from snowflake_sample_data.information_schema.tables
union
select * from util_db.information_schema.tables
);
CREATE OR REPLACE PROCEDURE DEMO_DB.PUBLIC.SNOWBALL(
db_name STRING,
schema_name STRING,
snowball_table STRING,
max_age_days FLOAT,
limit FLOAT
)
RETURNS VARIANT
LANGUAGE JAVASCRIPT
COMMENT = 'Collects table and column stats.'
EXECUTE AS OWNER
AS
$$
var validLimit = Math.max(LIMIT, 0); // prevent SQL syntax error caused by negative numbers
var sqlGenerateInserts = `
WITH snowball_tables AS (
SELECT CONCAT_WS('.', table_catalog, table_schema, table_name) AS full_table_name, *
FROM IDENTIFIER(?) -- <<DB_NAME>>.INFORMATION_SCHEMA.TABLES
),
snowball_columns AS (
SELECT CONCAT_WS('.', table_catalog, table_schema, table_name) AS full_table_name, *
FROM IDENTIFIER(?) -- <<DB_NAME>>.INFORMATION_SCHEMA.COLUMNS
),
snowball AS (
SELECT table_name, MAX(stats_run_date_time) AS stats_run_date_time
FROM IDENTIFIER(?) -- <<SNOWBALL_TABLE>> table
GROUP BY table_name
)
SELECT full_table_name, aprox_row_count,
CONCAT (
'INSERT INTO IDENTIFIER(''', ?, ''') ', -- SNOWBALL table
'(table_name,total_rows,table_last_altered,table_created,table_bytes,col_name,',
'col_data_type,col_hll,col_avg_length,col_null_cnt,col_min,col_max,col_top,col_mode,col_avg,stats_run_date_time)',
'SELECT ''', full_table_name, ''' AS table_name, ',
table_stats_sql,
', ARRAY_CONSTRUCT( ', col_name, ') AS col_name',
', ARRAY_CONSTRUCT( ', col_data_type, ') AS col_data_type',
', ARRAY_CONSTRUCT( ', col_hll, ') AS col_hll',
', ARRAY_CONSTRUCT( ', col_avg_length, ') AS col_avg_length',
', ARRAY_CONSTRUCT( ', col_null_cnt, ') AS col_null_cnt',
', ARRAY_CONSTRUCT( ', col_min, ') AS col_min',
', ARRAY_CONSTRUCT( ', col_max, ') AS col_max',
', ARRAY_CONSTRUCT( ', col_top, ') AS col_top',
', ARRAY_CONSTRUCT( ', col_MODE, ') AS col_MODE',
', ARRAY_CONSTRUCT( ', col_AVG, ') AS col_AVG',
', CURRENT_TIMESTAMP() AS stats_run_date_time ',
' FROM ', quoted_table_name
) AS insert_sql
FROM (
SELECT
tbl.full_table_name,
tbl.row_count AS aprox_row_count,
CONCAT ( '"', col.table_catalog, '"."', col.table_schema, '"."', col.table_name, '"' ) AS quoted_table_name,
CONCAT (
'COUNT(1) AS total_rows,''',
IFNULL( tbl.last_altered::VARCHAR, 'NULL'), ''' AS table_last_altered,''',
IFNULL( tbl.created::VARCHAR, 'NULL'), ''' AS table_created,',
IFNULL( tbl.bytes::VARCHAR, 'NULL'), ' AS table_bytes' ) AS table_stats_sql,
LISTAGG (
CONCAT ('''', col.full_table_name, '.', col.column_name, '''' ), ', '
) AS col_name,
LISTAGG ( CONCAT('''', col.data_type, '''' ), ', ' ) AS col_data_type,
LISTAGG ( CONCAT( ' HLL(', '"', col.column_name, '"',') ' ), ', ' ) AS col_hll,
LISTAGG ( CONCAT( ' AVG(ZEROIFNULL(LENGTH(', '"', col.column_name, '"','))) ' ), ', ' ) AS col_avg_length,
LISTAGG ( CONCAT( ' SUM( IFF( ', '"', col.column_name, '"',' IS NULL, 1, 0) ) ' ), ', ') AS col_null_cnt,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MODE(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_MODE,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MIN(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_min,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MAX(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_max,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' AVG(', '"', col.column_name,'"',') ' ), 'NULL' ), ', ' ) AS col_AVG,
LISTAGG ( CONCAT ( ' APPROX_TOP_K(', '"', col.column_name, '"', ', 100, 10000)' ), ', ' ) AS col_top
FROM snowball_tables tbl JOIN snowball_columns col ON col.full_table_name = tbl.full_table_name
LEFT OUTER JOIN snowball sb ON sb.table_name = tbl.full_table_name
WHERE (tbl.table_catalog, tbl.table_schema) = (?, ?)
AND ( sb.table_name IS NULL OR sb.stats_run_date_time < TIMESTAMPADD(DAY, - FLOOR(?), CURRENT_TIMESTAMP()) )
--AND tbl.row_count > 0 -- NB: also excludes views (table_type = 'VIEW')
GROUP BY tbl.full_table_name, aprox_row_count, quoted_table_name, table_stats_sql, stats_run_date_time
ORDER BY stats_run_date_time NULLS FIRST )
LIMIT ` + validLimit;
var tablesAnalysed = [];
var currentSql;
try {
currentSql = sqlGenerateInserts;
var generateInserts = snowflake.createStatement( {
sqlText: currentSql,
binds: [
`"${DB_NAME}".information_schema.tables`,
`"${DB_NAME}".information_schema.columns`,
SNOWBALL_TABLE, SNOWBALL_TABLE,
DB_NAME, SCHEMA_NAME, MAX_AGE_DAYS, LIMIT
]
} );
var insertStatements = generateInserts.execute();
// loop over generated INSERT statements and execute them
while (insertStatements.next()) {
var tableName = insertStatements.getColumnValue('FULL_TABLE_NAME');
currentSql = insertStatements.getColumnValue('INSERT_SQL');
var insertStatement = snowflake.createStatement( {
sqlText: currentSql,
binds: [ SNOWBALL_TABLE ]
} );
var insertResult = insertStatement.execute();
tablesAnalysed.push(tableName);
}
return { result: "SUCCESS", analysedTables: tablesAnalysed };
}
catch (err) {
return {
error: err,
analysedTables: tablesAnalysed,
sql: currentSql
};
}
$$;
call DEMO_DB.PUBLIC.SNOWBALL(
'SNOWFLAKE_SAMPLE_DATA',
'TPCH_SF1',
'DEMO_DB.PUBLIC.SNOWBALL',
1, -- evals tables not analysed for x days -- first time you run this doesn't matter.
1000 -- limits # of tables analysed
);

Answer 2

CREATE OR REPLACE PROCEDURE DEMO_DB.PUBLIC.SNOWBALL(
db_name STRING,
schema_name STRING,
snowball_table STRING,
max_age_days FLOAT,
limit FLOAT
)
RETURNS VARIANT
LANGUAGE JAVASCRIPT
COMMENT = 'Collects table and column stats.'
EXECUTE AS OWNER
AS
$$
var validLimit = Math.max(LIMIT, 0); // prevent SQL syntax error caused by negative numbers
var sqlGenerateInserts = `
WITH snowball_tables AS (
SELECT CONCAT_WS('.', table_catalog, table_schema, table_name) AS full_table_name, *
FROM IDENTIFIER(?) -- <<DB_NAME>>.INFORMATION_SCHEMA.TABLES
),
snowball_columns AS (
SELECT CONCAT_WS('.', table_catalog, table_schema, table_name) AS full_table_name, *
FROM IDENTIFIER(?) -- <<DB_NAME>>.INFORMATION_SCHEMA.COLUMNS
),
snowball AS (
SELECT table_name, MAX(stats_run_date_time) AS stats_run_date_time
FROM IDENTIFIER(?) -- <<SNOWBALL_TABLE>> table
GROUP BY table_name
)
SELECT full_table_name, aprox_row_count,
CONCAT (
'INSERT INTO IDENTIFIER(''', ?, ''') ', -- SNOWBALL table
'(table_name,total_rows,table_last_altered,table_created,table_bytes,col_name,',
'col_data_type,col_hll,col_avg_length,col_null_cnt,col_min,col_max,col_top,col_mode,col_avg,stats_run_date_time)',
'SELECT ''', full_table_name, ''' AS table_name, ',
table_stats_sql,
', ARRAY_CONSTRUCT( ', col_name, ') AS col_name',
', ARRAY_CONSTRUCT( ', col_data_type, ') AS col_data_type',
', ARRAY_CONSTRUCT( ', col_hll, ') AS col_hll',
', ARRAY_CONSTRUCT( ', col_avg_length, ') AS col_avg_length',
', ARRAY_CONSTRUCT( ', col_null_cnt, ') AS col_null_cnt',
', ARRAY_CONSTRUCT( ', col_min, ') AS col_min',
', ARRAY_CONSTRUCT( ', col_max, ') AS col_max',
', ARRAY_CONSTRUCT( ', col_top, ') AS col_top',
', ARRAY_CONSTRUCT( ', col_MODE, ') AS col_MODE',
', ARRAY_CONSTRUCT( ', col_AVG, ') AS col_AVG',
', CURRENT_TIMESTAMP() AS stats_run_date_time ',
' FROM ', quoted_table_name
) AS insert_sql
FROM (
SELECT
tbl.full_table_name,
tbl.row_count AS aprox_row_count,
CONCAT ( '"', col.table_catalog, '"."', col.table_schema, '"."', col.table_name, '"' ) AS quoted_table_name,
CONCAT (
'COUNT(1) AS total_rows,''',
IFNULL( tbl.last_altered::VARCHAR, 'NULL'), ''' AS table_last_altered,''',
IFNULL( tbl.created::VARCHAR, 'NULL'), ''' AS table_created,',
IFNULL( tbl.bytes::VARCHAR, 'NULL'), ' AS table_bytes' ) AS table_stats_sql,
LISTAGG (
CONCAT ('''', col.full_table_name, '.', col.column_name, '''' ), ', '
) AS col_name,
LISTAGG ( CONCAT('''', col.data_type, '''' ), ', ' ) AS col_data_type,
LISTAGG ( CONCAT( ' HLL(', '"', col.column_name, '"',') ' ), ', ' ) AS col_hll,
LISTAGG ( CONCAT( ' AVG(ZEROIFNULL(LENGTH(', '"', col.column_name, '"','))) ' ), ', ' ) AS col_avg_length,
LISTAGG ( CONCAT( ' SUM( IFF( ', '"', col.column_name, '"',' IS NULL, 1, 0) ) ' ), ', ') AS col_null_cnt,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MODE(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_MODE,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MIN(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_min,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' MAX(', '"', col.column_name, '"', ') ' ), 'NULL' ), ', ' ) AS col_max,
LISTAGG ( IFF ( col.data_type = 'NUMBER', CONCAT ( ' AVG(', '"', col.column_name,'"',') ' ), 'NULL' ), ', ' ) AS col_AVG,
LISTAGG ( CONCAT ( ' APPROX_TOP_K(', '"', col.column_name, '"', ', 100, 10000)' ), ', ' ) AS col_top
FROM snowball_tables tbl JOIN snowball_columns col ON col.full_table_name = tbl.full_table_name
LEFT OUTER JOIN snowball sb ON sb.table_name = tbl.full_table_name
WHERE (tbl.table_catalog, tbl.table_schema) = (?, ?)
AND ( sb.table_name IS NULL OR sb.stats_run_date_time < TIMESTAMPADD(DAY, - FLOOR(?), CURRENT_TIMESTAMP()) )
--AND tbl.row_count > 0 -- NB: also excludes views (table_type = 'VIEW')
GROUP BY tbl.full_table_name, aprox_row_count, quoted_table_name, table_stats_sql, stats_run_date_time
ORDER BY stats_run_date_time NULLS FIRST )
LIMIT ` + validLimit;
var tablesAnalysed = [];
var currentSql;
try {
currentSql = sqlGenerateInserts;
var generateInserts = snowflake.createStatement( {
sqlText: currentSql,
binds: [
`"${DB_NAME}".information_schema.tables`,
`"${DB_NAME}".information_schema.columns`,
SNOWBALL_TABLE, SNOWBALL_TABLE,
DB_NAME, SCHEMA_NAME, MAX_AGE_DAYS, LIMIT
]
} );
var insertStatements = generateInserts.execute();
// loop over generated INSERT statements and execute them
while (insertStatements.next()) {
var tableName = insertStatements.getColumnValue('FULL_TABLE_NAME');
currentSql = insertStatements.getColumnValue('INSERT_SQL');
var insertStatement = snowflake.createStatement( {
sqlText: currentSql,
binds: [ SNOWBALL_TABLE ]
} );
var insertResult = insertStatement.execute();
tablesAnalysed.push(tableName);
}
return { result: "SUCCESS", analysedTables: tablesAnalysed };
}
catch (err) {
return {
error: err,
analysedTables: tablesAnalysed,
sql: currentSql
};
}
$$;
I've done somewhat of an overkill solution solving this.
SQL used supplied ... basically does everything you've asked for plus top 100 values, min,max, stddev, avg, null % to the column level for every table in ALL databases.
Oh yes and works out ALL PK/FK's returning not just the PK but the description instead.
Runs in seconds ... All sql available from a post in the community snowflake. Hit me up if you want the really smart stuff :-)
SQL here :
https://community.snowflake.com/s/group/0F90Z000000IOX5SAO/general-snowflake-community-help