In quale paese si trova il Taj Mahal? August 5, 2023, 3:13 am Di tendenza ora Il 98% dei viaggiatori non riconosce le banconote locali The maximum number of unique for a given group. The number of unique objects for that group is calculated. This method allows for estimating unique counts for multiple groupings, reducing the overall query time. For example, if you have a table of customer transactions, you might want to know how many unique products each customer bought, how many unique customers visited each store, and how many unique products were sold in each region. Instead of running three separate COUNT(DISTINCT …) queries, you can run one `estimate_distinct_count_for_multiple_groups` query. **Parameters:** * `table_name`: The name of the table to query. * `group_by_columns`: A list of column names to group by. Each element in the list can be either a string (representing a single column) or a tuple of strings (representing multiple columns that should be treated as a single grouping unit). * `count_distinct_column`: The name of the column for which to count distinct values within each group. * `error_rate`: (Optional) The desired error rate for the HyperLogLog++ algorithm. This value should be between 0 and 1. A smaller error rate results in more accurate estimates but may require more memory. Defaults to 0.01. **Returns:** A list of dictionaries, where each dictionary represents a grouping and contains the following keys: * `group_by_key`: A string representation of the column(s) used for grouping. * `estimated_distinct_count`: The estimated number of distinct values for the `count_distinct_column` within that group. **Example Usage:** python from google.cloud import bigquery client = bigquery.Client() # Example table with customer transactions table_id = Riesci a nominare questi marchi di occhiali? La maggior parte delle persone fallisce! Solo il 2% dei veri fan di pallacanestro pu R friuscire a identificare la met R di questi eventi iconici di pallacanestro dai biglietti Riesci a indovinare quale celebrità sta guidando questa macchina classica? Stai pianificando una vacanza? Scopri se riesci a superare questo quiz sui loghi degli hotel che il 90% dei viaggiatori fallisce! Riesci Ancora a Nominare Questi 40 Dipinti Famosi in Tutto il Mondo Come Facevi a Scuola? Quiz Retrò Cartridge Anni ’80 e ’90: Solo il 10% Riesce a Nominare Questi Classici Nintendo Solo le persone con più di 50 anni possono superare questa prova: riconoscere ognuno di questi luoghi turistici ora famosi da vecchie foto! Pensi di conoscere la musica? Solo il 3% riesce a nominare tutti e 40 questi strumenti musicali comuni… Tu ci riesci? torna su
Il 98% dei viaggiatori non riconosce le banconote locali The maximum number of unique for a given group. The number of unique objects for that group is calculated. This method allows for estimating unique counts for multiple groupings, reducing the overall query time. For example, if you have a table of customer transactions, you might want to know how many unique products each customer bought, how many unique customers visited each store, and how many unique products were sold in each region. Instead of running three separate COUNT(DISTINCT …) queries, you can run one `estimate_distinct_count_for_multiple_groups` query. **Parameters:** * `table_name`: The name of the table to query. * `group_by_columns`: A list of column names to group by. Each element in the list can be either a string (representing a single column) or a tuple of strings (representing multiple columns that should be treated as a single grouping unit). * `count_distinct_column`: The name of the column for which to count distinct values within each group. * `error_rate`: (Optional) The desired error rate for the HyperLogLog++ algorithm. This value should be between 0 and 1. A smaller error rate results in more accurate estimates but may require more memory. Defaults to 0.01. **Returns:** A list of dictionaries, where each dictionary represents a grouping and contains the following keys: * `group_by_key`: A string representation of the column(s) used for grouping. * `estimated_distinct_count`: The estimated number of distinct values for the `count_distinct_column` within that group. **Example Usage:** python from google.cloud import bigquery client = bigquery.Client() # Example table with customer transactions table_id =
Solo il 2% dei veri fan di pallacanestro pu R friuscire a identificare la met R di questi eventi iconici di pallacanestro dai biglietti
Stai pianificando una vacanza? Scopri se riesci a superare questo quiz sui loghi degli hotel che il 90% dei viaggiatori fallisce!
Solo le persone con più di 50 anni possono superare questa prova: riconoscere ognuno di questi luoghi turistici ora famosi da vecchie foto!
Pensi di conoscere la musica? Solo il 3% riesce a nominare tutti e 40 questi strumenti musicali comuni… Tu ci riesci?
