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Snowflake\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EQuesto quickstart Powered by Tasty Bytes - Da zero a Snowflake è dedicato alla trasformazione.\u003C/p\u003E\n","\u003Cp\u003EIn questo quickstart esamineremo un’ampia gamma di funzionalità di Snowflake, tra cui Zero-Copy Cloning e Time Travel, per soddisfare un requisito aziendale di Tasty Bytes.\u003C/p\u003E\n","\u003Ch3\u003EPrerequisiti\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EPrima di iniziare, assicurati di avere completato il \u003Ca href=\"/it/developers/guides/tasty-bytes-introduction-it/\"\u003E\u003Cstrong\u003Equickstart Introduzione a Tasty Bytes\u003C/strong\u003E\u003C/a\u003E, che spiega nei dettagli come configurare un account di prova e implementare l’ambiente base di Tasty Bytes necessario per completare questo quickstart.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ECosa imparerai\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ECome clonare una tabella\u003C/li\u003E\u003Cli\u003ECome utilizzare la cache dei set di risultati di Snowflake\u003C/li\u003E\u003Cli\u003ECome aggiungere una colonna a una tabella\u003C/li\u003E\u003Cli\u003ECome aggiornare i dati in una colonna\u003C/li\u003E\u003Cli\u003ECome utilizzare Time Travel\u003C/li\u003E\u003Cli\u003ECome fare lo swap, il drop e l’undrop di una tabella\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ECosa realizzerai\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EComprenderai alcune importanti funzionalità di trasformazione di Snowflake\u003C/li\u003E\u003Cli\u003EUn clone di sviluppo di una tabella di produzione\u003C/li\u003E\u003Cli\u003EUna nuova colonna in una tabella con le età calcolate dei food truck in anni\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003ECreare un foglio di lavoro e copiare il codice SQL\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EIn questo quickstart seguiremo la storia del cliente Tasty Bytes attraverso un foglio di lavoro SQL di Snowsight, utilizzando questa pagina come guida completa di commenti aggiuntivi, immagini e link alla documentazione.\u003C/p\u003E\n","\u003Cp\u003EIn questa sezione vedremo nei dettagli come accedere a Snowflake, creare un nuovo foglio di lavoro, rinominarlo, copiare da GitHub il codice SQL che utilizzeremo in questo quickstart e incollarlo nel foglio di lavoro.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Accedere a Snowflake tramite URL\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EApri una finestra del browser e inserisci l’URL del tuo account Snowflake\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 2 - Effettuare l’accesso a Snowflake\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EAccedi al tuo account Snowflake.\n\u003Cul\u003E\u003Cli\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/log_into_snowflake.gif\" alt=\"assets/log_into_snowflake.gif\"\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 3 - Accedere ai fogli di lavoro\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EFai clic sulla scheda Worksheets nella barra di navigazione sulla sinistra.\n\u003Cul\u003E\u003Cli\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/worksheet_tab.png\" alt=\"assets/worksheet_tab.png\"\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 4 - Creare un foglio di lavoro\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ENella scheda Worksheets, fai clic sul pulsante “+” nell’angolo superiore destro di Snowsight e scegli “SQL Worksheet”\n\u003Cul\u003E\u003Cli\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/+_sqlworksheet.png\" alt=\"assets/+_sqlworksheet.png\"\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 5 - Rinominare un foglio di lavoro\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ERinomina il foglio di lavoro facendo clic sul nome generato automaticamente (data e ora) e inserendo “Tasty Bytes - Transformation”.\n\u003Cul\u003E\u003Cli\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/rename_worksheet_tasty_bytes_setup.gif\" alt=\"assets/rename_worksheet_tasty_bytes_setup.gif\"\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 6 - Accedere al codice SQL di questo quickstart in GitHub\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EFai clic sul pulsante qui sotto, che ti porterà al file SQL di Tasty Bytes archiviato su GitHub. <button>\u003Ca href=\"https://github.com/Snowflake-Labs/sf-samples/blob/main/samples/tasty_bytes/tb_zts_transformation.sql\"\u003Etb_zts_transformation\u003C/a\u003E</button>\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 7 - Copiare la configurazione SQL da GitHub\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EIn GitHub, vai sul lato destro e fai clic su “Copy raw contents”. Tutto il codice SQL necessario verrà copiato nei tuoi Appunti.\n\u003Cul\u003E\u003Cli\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/github_copy_raw_contents.png\" alt=\"assets/github_copy_raw_contents.png\"\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 8 - Incollare la configurazione SQL da GitHub nel tuo foglio di lavoro Snowflake\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ETorna a Snowsight e al foglio di lavoro che hai appena creato e incolla (\u003Cem\u003ECMD + V per Mac o CTRL + V per Windows\u003C/em\u003E) il codice che abbiamo appena copiato da GitHub.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPassaggio 9 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EClonare istantaneamente una tabella di produzione per lo sviluppo\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003ENel quadro dell’analisi della flotta di food truck di Tasty Bytes, il nostro sviluppatore è stato incaricato di aggiungere alla tabella dei furgoni una colonna calcolata con l’età dei veicoli.\u003C/p\u003E\n","\u003Cp\u003ECome tutti gli sviluppatori competenti, sappiamo che non possiamo lavorare su una tabella di produzione, quindi per prima cosa dobbiamo creare un ambiente di sviluppo che riproduca quello di produzione.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Creare un clone dell’ambiente di produzione\u003C/h3\u003E\n","\u003Cp\u003EGrazie all’architettura unica di Snowflake, possiamo creare istantaneamente uno snapshot della tabella \u003Ccode\u003Eraw_pos.truck\u003C/code\u003E di produzione utilizzando la funzionalità \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/create-clone\"\u003ECLONE\u003C/a\u003E e chiamarlo \u003Ccode\u003Eraw_pos.truck_dev\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EOra eseguiamo la prossima serie di query per impostare il contesto del nostro ruolo \u003Ccode\u003Etasty_dev\u003C/code\u003E e creare il clone della tabella; nota che non abbiamo bisogno di impostare il contesto del warehouse, poiché la clonazione non lo richiede.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUSE ROLE tasty_dev;\n\nCREATE OR REPLACE TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \n    CLONE frostbyte_tasty_bytes.raw_pos.truck; \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/3.1.truck_dev_clone.png\" alt=\"assets/3.1.truck_dev_clone.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EZero-Copy Cloning\u003C/strong\u003E: crea una copia di un database, di uno schema o di una tabella. Al momento della creazione del clone viene creato uno snapshot dei dati contenuti nell’oggetto sorgente, che viene messo a disposizione dell’oggetto clonato. L’oggetto clonato è scrivibile ed è indipendente dalla sorgente del clone. In altri termini, le modifiche apportate all’oggetto sorgente non si riflettono sull’oggetto clone e viceversa.\u003C/p\u003E\n\u003Cblockquote\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EPassaggio 2 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003ETestare la cache dei set di risultati di Snowflake\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003ECon il nostro clone Zero-Copy istantaneamente disponibile, possiamo iniziare a utilizzarlo per sviluppare senza temere ripercussioni sull’ambiente di produzione. Tuttavia, prima di apportare qualsiasi modifica, eseguiamo alcune semplici query sul clone per testare la cache dei set di risultati di Snowflake.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Eseguire query sulla tabella clonata\u003C/h3\u003E\n","\u003Cp\u003EOra che vogliamo interrogare la tabella, dovremo usare il warehouse \u003Ccode\u003Etasty_dev_wh\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EEseguiamo le prossime due query con la seconda istruzione, che produce un set di risultati composto dai food truck con i rispettivi anni di produzione, marchi e modelli, assicurandoci di usare \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/constructs/order-by\"\u003EORDER BY\u003C/a\u003E per ordinare i risultati in base alla colonna \u003Ccode\u003Etruck_id\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUSE WAREHOUSE tasty_dev_wh;\n\nSELECT \n    t.truck_id, \n    t.year, \n    t.make, \n    t.model \nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t \nORDER BY t.truck_id; \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.1.truck.png\" alt=\"assets/4.1.truck.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 2 - Ripetere la query\u003C/h3\u003E\n","\u003Cp\u003EPer testare la \u003Ca href=\"https://docs.snowflake.com/en/user-guide/querying-persisted-results\"\u003Ecache dei set di risultati\u003C/a\u003E di Snowflake, la nostra prossima query sarà identica a quella appena eseguita. Tuttavia, questa volta accederemo anche a Query Profile per evidenziare il fatto che ha restituito i risultati istantaneamente, poiché provenivano dalla cache dei set di risultati.\u003C/p\u003E\n","\u003Cp\u003EDopo avere eseguito la query riportata sotto, segui i passaggi nella schermata in figura per accedere a \u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-query-profile\"\u003EQuery Profile\u003C/a\u003E. Da Query Profile vedremo un singolo nodo con l’indicazione \u003Ccode\u003EQUERY RESULT REUSE\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT\n    t.truck_id,\n    t.year,\n    t.make,\n    t.model\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t\nORDER BY t.truck_id;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.2.1.truck.png\" alt=\"assets/4.2.1.truck.png\"\u003E \u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.2.2.cache.png\" alt=\"assets/4.2.2.cache.png\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003Easide positive\nSe un utente ripete una query che è già stata eseguita e i dati nelle tabelle non sono cambiati dall’ultima esecuzione della query, il risultato della query è lo stesso. Invece di eseguire nuovamente la query, Snowflake restituisce semplicemente lo stesso risultato fornito in precedenza.\u003C/p\u003E\n","\u003Cp\u003EQuesto può ridurre notevolmente il tempo necessario per le query, poiché Snowflake evita di eseguire nuovamente la query e recupera invece il risultato direttamente dalla cache.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EPassaggio 3 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EAggiornare i dati e calcolare l’età dei food truck\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EIn base all’output ottenuto sopra, per prima cosa dobbiamo correggere l’errore di battitura nei record Ford_ che abbiamo visto nella colonna \u003Ccode\u003Emake\u003C/code\u003E. Poi potremo iniziare a lavorare sul calcolo che ci fornirà l’età di ogni furgone.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Aggiornare i valori errati in una colonna\u003C/h3\u003E\n","\u003Cp\u003EPer iniziare questa sezione, correggiamo l’errore di battitura eseguendo la prossima query, che utilizza \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/update\"\u003EUPDATE\u003C/a\u003E per modificare le righe in \u003Ccode\u003Etruck_dev\u003C/code\u003E quando (\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/constructs/where\"\u003EWHERE\u003C/a\u003E) la marca è uguale a Ford_.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev \nSET make = 'Ford' \nWHERE make = 'Ford_';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/5.1.ford_.png\" alt=\"assets/5.1.ford_.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 2 - Creare il calcolo dell’età\u003C/h3\u003E\n","\u003Cp\u003EOra che abbiamo corretto l’errore di battitura, possiamo calcolare l’età in anni dei furgoni della nostra flotta. Esegui la prossima query, dove utilizzeremo \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/year\"\u003EYEAR\u003C/a\u003E e \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/current_date\"\u003ECURRENT_DATE\u003C/a\u003E per calcolare questo valore.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT\n    t.truck_id,\n    t.year,\n    t.make,\n    t.model,\n    (YEAR(CURRENT_DATE()) - t.year) AS truck_age_year\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/5.2.age.png\" alt=\"assets/5.2.age.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 3 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EAggiungere una colonna e aggiornarla\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EOra che abbiamo completato il calcolo dell’età dei furgoni in anni, aggiungiamo una nuova colonna alla tabella clonata per supportarlo e quindi aggiorniamo la colonna per riflettere i valori calcolati.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Aggiungere una colonna a una tabella\u003C/h3\u003E\n","\u003Cp\u003EPer iniziare, esegui la prossima query che utilizza \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/alter-table-column\"\u003EALTER TABLE… ADD COLUMN\u003C/a\u003E per creare una colonna \u003Ccode\u003Etruck_age\u003C/code\u003E vuota del \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/data-types-numeric\"\u003Etipo di dati NUMBER\u003C/a\u003E nella tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EQuesta query fornirà un risultato \u003Ccode\u003EStatement executed successfully\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EALTER TABLE frostbyte_tasty_bytes.raw_pos.truck_dev\n    ADD COLUMN truck_age NUMBER(4);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EPassaggio 2 - Aggiungere valori calcolati alla colonna\u003C/h3\u003E\n","\u003Cp\u003EDopo avere creato la colonna, possiamo avviare la prossima query che aggiornerà (\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/update\"\u003EUPDATE\u003C/a\u003E) la nuova colonna \u003Ccode\u003Etruck_age\u003C/code\u003E vuota utilizzando il calcolo dell’età del furgone che abbiamo creato nella sezione precedente.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev t\n    SET truck_age = (YEAR(CURRENT_DATE()) / t.year);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/6.2.update.png\" alt=\"assets/6.2.update.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 3 - Eseguire una query sulla nuova colonna\u003C/h3\u003E\n","\u003Cp\u003EDopo avere aggiornato i dati, eseguiamo una query rapida sulla tabella per vedere i risultati nella nuova colonna \u003Ccode\u003Etruck_age\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT\n    t.truck_id,\n    t.year,\n    t.truck_age\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/6.3.bad_data.png\" alt=\"assets/6.3.bad_data.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAhi ahi!\u003C/strong\u003E Per fortuna siamo sviluppatori intelligenti e non abbiamo rischiato di fare una cosa di questo genere in produzione.\u003C/p\u003E\n","\u003Cp\u003EEvidentemente abbiamo sbagliato il calcolo di \u003Ccode\u003Etruck_age\u003C/code\u003E inserendo una divisione al posto di una sottrazione. Dovremo risolvere questo problema nella prossima sezione.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 4 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EUtilizzare Time Travel per il disaster recovery dei dati\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EAnche se abbiamo fatto un errore, Snowflake offre molte funzionalità che possono aiutarci a salvare la situazione. In questo processo utilizzeremo Query History, le variabili SQL e Time Travel per ripristinare la tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E allo stato in cui si trovava prima di quell’istruzione pdate errata.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003Easide positive\nSnowflake Time Travel consente di accedere ai dati storici (ossia dati che sono stati modificati o cancellati) in qualsiasi momento entro un periodo definito.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EPassaggio 1 - Utilizzare Query History\u003C/h3\u003E\n","\u003Cp\u003EPer iniziare il processo di ripristino, esegui la prossima query, che utilizza la funzione \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/query_history\"\u003EQUERY_HISTORY\u003C/a\u003E di Snowflake per recuperare un elenco di tutte le istruzioni di aggiornamento che abbiamo eseguito sulla tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT \n   query_id,\n   query_text,\n   user_name,\n   query_type,\n   start_time\nFROM TABLE(frostbyte_tasty_bytes.information_schema.query_history())\nWHERE 1=1\n   AND query_type = 'UPDATE'\n   AND query_text LIKE '%frostbyte_tasty_bytes.raw_pos.truck_dev%'\nORDER BY start_time DESC;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/7.1.query_history.png\" alt=\"assets/7.1.query_history.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 2 - Impostare una variabile SQL\u003C/h3\u003E\n","\u003Cp\u003ECome previsto, vediamo la correzione dell’errore di battitura e l’aggiornamento del calcolo errato, accompagnati dai rispettivi query_id univoci. Esegui la prossima query, che crea una variabile SQL \u003Ccode\u003Equery_id\u003C/code\u003E che utilizzeremo per ripristinare le modifiche mediante Time Travel nel prossimo passaggio.\u003C/p\u003E\n","\u003Cp\u003EDopo l’esecuzione riceverai un risultato \u003Ccode\u003EStatement executed successfully\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESET query_id = \n(\n    SELECT TOP 1 query_id\n    FROM TABLE(frostbyte_tasty_bytes.information_schema.query_history())\n    WHERE 1=1\n        AND query_type = 'UPDATE'\n        AND query_text LIKE '%SET truck_age = (YEAR(CURRENT_DATE()) / t.year);'\n    ORDER BY start_time DESC\n);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EPassaggio 3 - Utilizzare Time Travel per ripristinare la tabella\u003C/h3\u003E\n","\u003Cp\u003ECon la nostra query_id errata memorizzata come variabile, possiamo eseguire la prossima query, che utilizza Time Travel per sostituire la tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E con la versione che esisteva prima (\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/constructs/at-before\"\u003EBEFORE\u003C/a\u003E) dell’istruzione query_id errata.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \n    AS \nSELECT * FROM frostbyte_tasty_bytes.raw_pos.truck_dev \nBEFORE(STATEMENT => $query_id); \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/7.3.time_travel.png\" alt=\"assets/7.3.time_travel.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EDi seguito sono riportate le altre opzioni disponibili per le istruzioni Time Travel.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003Easide positive\n\u003Cstrong\u003EAT:\u003C/strong\u003E la parola chiave AT indica che la richiesta include tutte le eventuali modifiche apportate da un’istruzione o una transazione con data e ora uguali al parametro specificato.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBEFORE:\u003C/strong\u003E la parola chiave BEFORE indica che la richiesta si riferisce a un punto immediatamente precedente al parametro specificato.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETIMESTAMP:\u003C/strong\u003E specifica una data e un’ora esatta da utilizzare per Time Travel.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EOFFSET:\u003C/strong\u003E specifica la differenza in secondi dall’orario attuale da utilizzare per Time Travel.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESTATEMENT:\u003C/strong\u003E specifica la query_id di un’istruzione da utilizzare come punto di riferimento per Time Travel.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EPassaggio 4 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EPromuovere da sviluppo a produzione\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EOra che la tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E è tornata allo stato in cui si trovava prima della nostra istruzione di aggiornamento errata, possiamo assicurarci che la colonna venga aggiornata correttamente. Poi promuoveremo la tabella con il calcolo corretto in produzione per completare il compito che ci è stato assegnato.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Aggiungere i valori calcolati correttamente alla colonna\u003C/h3\u003E\n","\u003Cp\u003EUtilizzando lo stesso processo di prima, esegui la prossima query, controllando attentamente di utilizzare la sottrazione invece della divisione.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev t\nSET truck_age = (YEAR(CURRENT_DATE()) - t.year);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/8.1.correct_update.png\" alt=\"assets/8.1.correct_update.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 2 - Scambiare la tabella dall’ambiente di sviluppo a quello di produzione\u003C/h3\u003E\n","\u003Cp\u003EOra che abbiamo completato tutte le operazioni in \u003Ccode\u003Etruck_dev\u003C/code\u003E, esegui le prossime due query, in cui per prima cosa assumiamo il ruolo \u003Ccode\u003Esysadmin\u003C/code\u003E, con privilegi più elevati. Come \u003Ccode\u003Esysadmin\u003C/code\u003E, la seconda query utilizza \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/alter-table\"\u003EALTER TABLE… SWAP WITH\u003C/a\u003E per promuovere la tabella \u003Ccode\u003Etruck_dev\u003C/code\u003E a \u003Ccode\u003Etruck\u003C/code\u003E e viceversa.\u003C/p\u003E\n","\u003Cp\u003EAl termine riceverai il risultato \u003Ccode\u003EStatement executed successfully.\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUSE ROLE sysadmin;\n\nALTER TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \n    SWAP WITH frostbyte_tasty_bytes.raw_pos.truck; \n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EPassaggio 3 - Convalidare in produzione\u003C/h3\u003E\n","\u003Cp\u003EPer verificare che il processo sia riuscito, diamo un’occhiata alla tabella di produzione \u003Ccode\u003Etruck\u003C/code\u003E per confermare che lo swap sia stato eseguito correttamente e che i risultati di \u003Ccode\u003Etruck_age\u003C/code\u003E siano validi.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT \n    t.truck_id, \n    t.year, \n    t.truck_age \nFROM frostbyte_tasty_bytes.raw_pos.truck t \nWHERE t.make = 'Ford';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/8.3.validate_prod.png\" alt=\"assets/8.3.validate_prod.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 4 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EFare il drop e l’undrop di tabelle\u003C/h2\u003E\n","\u003Ch3\u003EPanoramica\u003C/h3\u003E\n","\u003Cp\u003EPossiamo dire ufficialmente che il nostro sviluppatore ha completato il compito che gli era stato assegnato. Ora che la colonna \u003Ccode\u003Etruck_age\u003C/code\u003E è stata creata e calcolata correttamente, il nostro \u003Ccode\u003Esysadmin\u003C/code\u003E può eliminare la tabella superflua e consegnare il suo lavoro.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 1 - Fare il drop di una tabella\u003C/h3\u003E\n","\u003Cp\u003EPer rimuovere la tabella dal database, esegui la prossima query, che utilizza \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/drop-table\"\u003EDROP TABLE\u003C/a\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EDROP TABLE frostbyte_tasty_bytes.raw_pos.truck;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.1.drop.png\" alt=\"assets/9.1.drop.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAhi ahi!\u003C/strong\u003E Quel set di risultati dimostra che anche il nostro \u003Ccode\u003Esysadmin\u003C/code\u003E può fare errori. Abbiamo rimosso per errore la tabella di produzione \u003Ccode\u003Etruck\u003C/code\u003E e non la tabella di sviluppo \u003Ccode\u003Etruck_dev\u003C/code\u003E! Per fortuna, la funzionalità Time Travel di Snowflake può di nuovo venire in nostro aiuto.\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 2 - Fare l’undrop di una tabella\u003C/h3\u003E\n","\u003Cp\u003EPrima che altri sistemi possano risentirne, esegui al più presto la prossima query, che ripristinerà (\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/undrop-table\"\u003EUNDROP\u003C/a\u003E) la tabella \u003Ccode\u003Etruck\u003C/code\u003E rimossa.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EUNDROP TABLE frostbyte_tasty_bytes.raw_pos.truck;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.2.undrop.png\" alt=\"assets/9.2.undrop.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 3 - Fare il drop della tabella giusta\u003C/h3\u003E\n","\u003Cp\u003EVa bene, ora completiamo ufficialmente il lavoro eseguendo l’ultima query per fare il drop della tabella corretta \u003Ccode\u003Etruck_dev\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EDROP TABLE frostbyte_tasty_bytes.raw_pos.truck_dev;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.3.correctdrop.png\" alt=\"assets/9.3.correctdrop.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EPassaggio 4 - Fai clic su Next -->\u003C/h3\u003E\n","\u003Ch2\u003EConclusione e fasi successive\u003C/h2\u003E\n","\u003Ch3\u003EConclusione\u003C/h3\u003E\n","\u003Cp\u003EOttimo lavoro! Hai completato il quickstart Tasty Bytes - Da zero a Snowflake - Trasformazione.\u003C/p\u003E\n","\u003Cp\u003EIn questo quickstart hai:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EClonato una tabella\u003C/li\u003E\u003Cli\u003EUtilizzato la cache dei set di risultati di Snowflake\u003C/li\u003E\u003Cli\u003EAggiunto una colonna a una tabella\u003C/li\u003E\u003Cli\u003EAggiornato i dati in una colonna\u003C/li\u003E\u003Cli\u003EUtilizzato Time Travel per il disaster recovery dei dati\u003C/li\u003E\u003Cli\u003EFatto lo swap, il drop e l’undrop di una tabella\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003ESe desideri ripetere questo quickstart, usa gli script di ripristino alla fine del foglio di lavoro associato.\u003C/p\u003E\n","\u003Ch3\u003EFasi successive\u003C/h3\u003E\n","\u003Cp\u003EPer continuare il tuo percorso nel Data Cloud Snowflake, visita il link qui sotto per vedere tutti gli altri quickstart Powered by Tasty Bytes disponibili.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Ch3\u003E\u003Ca href=\"/it/developers/guides/tasty-bytes-introduction-it/\"\u003EQuickstart Powered by Tasty Bytes\u003C/a\u003E\u003C/h3\u003E\n\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Tasty Bytes - Da zero a Snowflake - Trasformazione","elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],":items":{},":itemsOrder":[],"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Trasformazione in Snowflake\r\n\r\n### Panoramica\r\nQuesto quickstart Powered by Tasty Bytes - Da zero a Snowflake è dedicato alla trasformazione.\r\n\r\nIn questo quickstart esamineremo un’ampia gamma di funzionalità di Snowflake, tra cui Zero-Copy Cloning e Time Travel, per soddisfare un requisito aziendale di Tasty Bytes.\r\n\r\n### Prerequisiti\r\n- Prima di iniziare, assicurati di avere completato il [**quickstart Introduzione a Tasty Bytes**](/it/developers/guides/tasty-bytes-introduction-it/), che spiega nei dettagli come configurare un account di prova e implementare l’ambiente base di Tasty Bytes necessario per completare questo quickstart.\r\n\r\n### Cosa imparerai\r\n- Come clonare una tabella\r\n- Come utilizzare la cache dei set di risultati di Snowflake\r\n- Come aggiungere una colonna a una tabella\r\n- Come aggiornare i dati in una colonna\r\n- Come utilizzare Time Travel\r\n- Come fare lo swap, il drop e l’undrop di una tabella\r\n\r\n### Cosa realizzerai\r\n- Comprenderai alcune importanti funzionalità di trasformazione di Snowflake \r\n- Un clone di sviluppo di una tabella di produzione\r\n- Una nuova colonna in una tabella con le età calcolate dei food truck in anni\r\n\r\n\r\n## Creare un foglio di lavoro e copiare il codice SQL\r\n\r\n### Panoramica\r\nIn questo quickstart seguiremo la storia del cliente Tasty Bytes attraverso un foglio di lavoro SQL di Snowsight, utilizzando questa pagina come guida completa di commenti aggiuntivi, immagini e link alla documentazione.\r\n\r\nIn questa sezione vedremo nei dettagli come accedere a Snowflake, creare un nuovo foglio di lavoro, rinominarlo, copiare da GitHub il codice SQL che utilizzeremo in questo quickstart e incollarlo nel foglio di lavoro.\r\n\r\n### Passaggio 1 - Accedere a Snowflake tramite URL\r\n- Apri una finestra del browser e inserisci l’URL del tuo account Snowflake \r\n\r\n### Passaggio 2 - Effettuare l’accesso a Snowflake\r\n- Accedi al tuo account Snowflake.\r\n    - ![assets/log_into_snowflake.gif](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/log_into_snowflake.gif)\r\n\r\n### Passaggio 3 - Accedere ai fogli di lavoro\r\n- Fai clic sulla scheda Worksheets nella barra di navigazione sulla sinistra.\r\n    - ![assets/worksheet_tab.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/worksheet_tab.png)\r\n\r\n### Passaggio 4 - Creare un foglio di lavoro\r\n- Nella scheda Worksheets, fai clic sul pulsante “+” nell’angolo superiore destro di Snowsight e scegli “SQL Worksheet”\r\n    - ![assets/+_sqlworksheet.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/+_sqlworksheet.png)\r\n\r\n### Passaggio 5 - Rinominare un foglio di lavoro\r\n- Rinomina il foglio di lavoro facendo clic sul nome generato automaticamente (data e ora) e inserendo “Tasty Bytes - Transformation”.\r\n    - ![assets/rename_worksheet_tasty_bytes_setup.gif](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/rename_worksheet_tasty_bytes_setup.gif)\r\n\r\n### Passaggio 6 - Accedere al codice SQL di questo quickstart in GitHub\r\n- Fai clic sul pulsante qui sotto, che ti porterà al file SQL di Tasty Bytes archiviato su GitHub. \u003Cbutton\u003E[tb_zts_transformation](https://github.com/Snowflake-Labs/sf-samples/blob/main/samples/tasty_bytes/tb_zts_transformation.sql)\u003C/button\u003E\r\n\r\n### Passaggio 7 - Copiare la configurazione SQL da GitHub\r\n- In GitHub, vai sul lato destro e fai clic su “Copy raw contents”. Tutto il codice SQL necessario verrà copiato nei tuoi Appunti.\r\n    - ![assets/github_copy_raw_contents.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/github_copy_raw_contents.png)\r\n\r\n### Passaggio 8 - Incollare la configurazione SQL da GitHub nel tuo foglio di lavoro Snowflake\r\n- Torna a Snowsight e al foglio di lavoro che hai appena creato e incolla (*CMD + V per Mac o CTRL + V per Windows*) il codice che abbiamo appena copiato da GitHub.\r\n\r\n### Passaggio 9 - Fai clic su Next --\u003E\r\n\r\n## Clonare istantaneamente una tabella di produzione per lo sviluppo\r\n\r\n### Panoramica\r\nNel quadro dell’analisi della flotta di food truck di Tasty Bytes, il nostro sviluppatore è stato incaricato di aggiungere alla tabella dei furgoni una colonna calcolata con l’età dei veicoli. \r\n \r\nCome tutti gli sviluppatori competenti, sappiamo che non possiamo lavorare su una tabella di produzione, quindi per prima cosa dobbiamo creare un ambiente di sviluppo che riproduca quello di produzione.\r\n\r\n### Passaggio 1 - Creare un clone dell’ambiente di produzione\r\nGrazie all’architettura unica di Snowflake, possiamo creare istantaneamente uno snapshot della tabella `raw_pos.truck` di produzione utilizzando la funzionalità [CLONE](https://docs.snowflake.com/en/sql-reference/sql/create-clone) e chiamarlo `raw_pos.truck_dev`.\r\n\r\nOra eseguiamo la prossima serie di query per impostare il contesto del nostro ruolo `tasty_dev` e creare il clone della tabella; nota che non abbiamo bisogno di impostare il contesto del warehouse, poiché la clonazione non lo richiede.\r\n\r\n``` \r\nUSE ROLE tasty_dev;\r\n\r\nCREATE OR REPLACE TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \r\n    CLONE frostbyte_tasty_bytes.raw_pos.truck; \r\n``` \r\n![assets/3.1.truck_dev_clone.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/3.1.truck_dev_clone.png)\r\n\r\n**Zero-Copy Cloning**: crea una copia di un database, di uno schema o di una tabella. Al momento della creazione del clone viene creato uno snapshot dei dati contenuti nell’oggetto sorgente, che viene messo a disposizione dell’oggetto clonato. L’oggetto clonato è scrivibile ed è indipendente dalla sorgente del clone. In altri termini, le modifiche apportate all’oggetto sorgente non si riflettono sull’oggetto clone e viceversa. \r\n\u003E\r\n\r\n### Passaggio 2 - Fai clic su Next --\u003E\r\n\r\n## Testare la cache dei set di risultati di Snowflake\r\n\r\n### Panoramica\r\nCon il nostro clone Zero-Copy istantaneamente disponibile, possiamo iniziare a utilizzarlo per sviluppare senza temere ripercussioni sull’ambiente di produzione. Tuttavia, prima di apportare qualsiasi modifica, eseguiamo alcune semplici query sul clone per testare la cache dei set di risultati di Snowflake.\r\n\r\n### Passaggio 1 - Eseguire query sulla tabella clonata\r\nOra che vogliamo interrogare la tabella, dovremo usare il warehouse `tasty_dev_wh`. \r\n\r\nEseguiamo le prossime due query con la seconda istruzione, che produce un set di risultati composto dai food truck con i rispettivi anni di produzione, marchi e modelli, assicurandoci di usare [ORDER BY](https://docs.snowflake.com/en/sql-reference/constructs/order-by) per ordinare i risultati in base alla colonna `truck_id`.\r\n\r\n``` \r\nUSE WAREHOUSE tasty_dev_wh;\r\n\r\nSELECT \r\n    t.truck_id, \r\n    t.year, \r\n    t.make, \r\n    t.model \r\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t \r\nORDER BY t.truck_id; \r\n```\r\n\r\n![assets/4.1.truck.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.1.truck.png)\r\n\r\n### Passaggio 2 - Ripetere la query\r\nPer testare la [cache dei set di risultati](https://docs.snowflake.com/en/user-guide/querying-persisted-results) di Snowflake, la nostra prossima query sarà identica a quella appena eseguita. Tuttavia, questa volta accederemo anche a Query Profile per evidenziare il fatto che ha restituito i risultati istantaneamente, poiché provenivano dalla cache dei set di risultati.\r\n\r\nDopo avere eseguito la query riportata sotto, segui i passaggi nella schermata in figura per accedere a [Query Profile](https://docs.snowflake.com/en/user-guide/ui-query-profile). Da Query Profile vedremo un singolo nodo con l’indicazione `QUERY RESULT REUSE`.\r\n\r\n```\r\nSELECT\r\n    t.truck_id,\r\n    t.year,\r\n    t.make,\r\n    t.model\r\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t\r\nORDER BY t.truck_id;\r\n```\r\n\r\n![assets/4.2.1.truck.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.2.1.truck.png) ![assets/4.2.2.cache.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/4.2.2.cache.png)\r\n\r\n\u003Easide positive\r\nSe un utente ripete una query che è già stata eseguita e i dati nelle tabelle non sono cambiati dall’ultima esecuzione della query, il risultato della query è lo stesso. Invece di eseguire nuovamente la query, Snowflake restituisce semplicemente lo stesso risultato fornito in precedenza. \r\n\u003E         \r\n\u003EQuesto può ridurre notevolmente il tempo necessario per le query, poiché Snowflake evita di eseguire nuovamente la query e recupera invece il risultato direttamente dalla cache.\r\n\u003E\r\n\r\n### Passaggio 3 - Fai clic su Next --\u003E\r\n\r\n## Aggiornare i dati e calcolare l’età dei food truck\r\n\r\n### Panoramica\r\nIn base all’output ottenuto sopra, per prima cosa dobbiamo correggere l’errore di battitura nei record Ford_ che abbiamo visto nella colonna `make`. Poi potremo iniziare a lavorare sul calcolo che ci fornirà l’età di ogni furgone.\r\n\r\n### Passaggio 1 - Aggiornare i valori errati in una colonna\r\nPer iniziare questa sezione, correggiamo l’errore di battitura eseguendo la prossima query, che utilizza [UPDATE](https://docs.snowflake.com/en/sql-reference/sql/update) per modificare le righe in `truck_dev` quando ([WHERE](https://docs.snowflake.com/en/sql-reference/constructs/where)) la marca è uguale a Ford_.\r\n\r\n```\r\nUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev \r\nSET make = 'Ford' \r\nWHERE make = 'Ford_';\r\n```\r\n\r\n![assets/5.1.ford_.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/5.1.ford_.png)\r\n\r\n### Passaggio 2 - Creare il calcolo dell’età\r\nOra che abbiamo corretto l’errore di battitura, possiamo calcolare l’età in anni dei furgoni della nostra flotta. Esegui la prossima query, dove utilizzeremo [YEAR](https://docs.snowflake.com/en/sql-reference/functions/year) e [CURRENT_DATE](https://docs.snowflake.com/en/sql-reference/functions/current_date) per calcolare questo valore.\r\n\r\n```\r\nSELECT\r\n    t.truck_id,\r\n    t.year,\r\n    t.make,\r\n    t.model,\r\n    (YEAR(CURRENT_DATE()) - t.year) AS truck_age_year\r\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t;\r\n```\r\n\r\n![assets/5.2.age.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/5.2.age.png)\r\n\r\n### Passaggio 3 - Fai clic su Next --\u003E\r\n\r\n## Aggiungere una colonna e aggiornarla\r\n\r\n### Panoramica\r\nOra che abbiamo completato il calcolo dell’età dei furgoni in anni, aggiungiamo una nuova colonna alla tabella clonata per supportarlo e quindi aggiorniamo la colonna per riflettere i valori calcolati.\r\n\r\n### Passaggio 1 - Aggiungere una colonna a una tabella\r\nPer iniziare, esegui la prossima query che utilizza [ALTER TABLE… ADD COLUMN](https://docs.snowflake.com/en/sql-reference/sql/alter-table-column) per creare una colonna `truck_age` vuota del [tipo di dati NUMBER](https://docs.snowflake.com/en/sql-reference/data-types-numeric) nella tabella `truck_dev`. \r\n\r\nQuesta query fornirà un risultato `Statement executed successfully`.\r\n\r\n```\r\nALTER TABLE frostbyte_tasty_bytes.raw_pos.truck_dev\r\n    ADD COLUMN truck_age NUMBER(4);\r\n```\r\n\r\n### Passaggio 2 - Aggiungere valori calcolati alla colonna\r\nDopo avere creato la colonna, possiamo avviare la prossima query che aggiornerà ([UPDATE](https://docs.snowflake.com/en/sql-reference/sql/update)) la nuova colonna `truck_age` vuota utilizzando il calcolo dell’età del furgone che abbiamo creato nella sezione precedente. \r\n```\r\nUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev t\r\n    SET truck_age = (YEAR(CURRENT_DATE()) / t.year);\r\n``` \r\n![assets/6.2.update.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/6.2.update.png)\r\n\r\n### Passaggio 3 - Eseguire una query sulla nuova colonna\r\nDopo avere aggiornato i dati, eseguiamo una query rapida sulla tabella per vedere i risultati nella nuova colonna `truck_age`. \r\n```\r\nSELECT\r\n    t.truck_id,\r\n    t.year,\r\n    t.truck_age\r\nFROM frostbyte_tasty_bytes.raw_pos.truck_dev t;\r\n``` \r\n![assets/6.3.bad_data.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/6.3.bad_data.png)\r\n\r\n**Ahi ahi!** Per fortuna siamo sviluppatori intelligenti e non abbiamo rischiato di fare una cosa di questo genere in produzione. \r\n\r\nEvidentemente abbiamo sbagliato il calcolo di `truck_age` inserendo una divisione al posto di una sottrazione. Dovremo risolvere questo problema nella prossima sezione.\r\n\r\n### Passaggio 4 - Fai clic su Next --\u003E\r\n\r\n## Utilizzare Time Travel per il disaster recovery dei dati\r\n\r\n### Panoramica\r\nAnche se abbiamo fatto un errore, Snowflake offre molte funzionalità che possono aiutarci a salvare la situazione. In questo processo utilizzeremo Query History, le variabili SQL e Time Travel per ripristinare la tabella `truck_dev` allo stato in cui si trovava prima di quell’istruzione pdate errata.\r\n\r\n\u003Easide positive \r\nSnowflake Time Travel consente di accedere ai dati storici (ossia dati che sono stati modificati o cancellati) in qualsiasi momento entro un periodo definito.\r\n\u003E\r\n\r\n### Passaggio 1 - Utilizzare Query History\r\nPer iniziare il processo di ripristino, esegui la prossima query, che utilizza la funzione [QUERY_HISTORY](https://docs.snowflake.com/en/sql-reference/functions/query_history) di Snowflake per recuperare un elenco di tutte le istruzioni di aggiornamento che abbiamo eseguito sulla tabella `truck_dev`.\r\n ```\r\nSELECT \r\n    query_id,\r\n    query_text,\r\n    user_name,\r\n    query_type,\r\n    start_time\r\nFROM TABLE(frostbyte_tasty_bytes.information_schema.query_history())\r\nWHERE 1=1\r\n    AND query_type = 'UPDATE'\r\n    AND query_text LIKE '%frostbyte_tasty_bytes.raw_pos.truck_dev%'\r\nORDER BY start_time DESC;\r\n``` \r\n![assets/7.1.query_history.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/7.1.query_history.png)\r\n\r\n### Passaggio 2 - Impostare una variabile SQL\r\nCome previsto, vediamo la correzione dell’errore di battitura e l’aggiornamento del calcolo errato, accompagnati dai rispettivi query_id univoci. Esegui la prossima query, che crea una variabile SQL `query_id` che utilizzeremo per ripristinare le modifiche mediante Time Travel nel prossimo passaggio. \r\n\r\nDopo l’esecuzione riceverai un risultato `Statement executed successfully`. \r\n```\r\nSET query_id = \r\n(\r\n    SELECT TOP 1 query_id\r\n    FROM TABLE(frostbyte_tasty_bytes.information_schema.query_history())\r\n    WHERE 1=1\r\n        AND query_type = 'UPDATE'\r\n        AND query_text LIKE '%SET truck_age = (YEAR(CURRENT_DATE()) / t.year);'\r\n    ORDER BY start_time DESC\r\n);\r\n```\r\n\r\n### Passaggio 3 - Utilizzare Time Travel per ripristinare la tabella\r\nCon la nostra query_id errata memorizzata come variabile, possiamo eseguire la prossima query, che utilizza Time Travel per sostituire la tabella `truck_dev` con la versione che esisteva prima ([BEFORE](https://docs.snowflake.com/en/sql-reference/constructs/at-before)) dell’istruzione query_id errata. \r\n\r\n``` \r\nCREATE OR REPLACE TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \r\n    AS \r\nSELECT * FROM frostbyte_tasty_bytes.raw_pos.truck_dev \r\nBEFORE(STATEMENT =\u003E $query_id); \r\n``` \r\n![assets/7.3.time_travel.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/7.3.time_travel.png)\r\n\r\nDi seguito sono riportate le altre opzioni disponibili per le istruzioni Time Travel.\r\n\u003Easide positive\r\n**AT:** la parola chiave AT indica che la richiesta include tutte le eventuali modifiche apportate da un’istruzione o una transazione con data e ora uguali al parametro specificato.\r\n\u003E\r\n\u003E**BEFORE:** la parola chiave BEFORE indica che la richiesta si riferisce a un punto immediatamente precedente al parametro specificato.\r\n\u003E\r\n\u003E**TIMESTAMP:** specifica una data e un’ora esatta da utilizzare per Time Travel.\r\n\u003E\r\n\u003E**OFFSET:** specifica la differenza in secondi dall’orario attuale da utilizzare per Time Travel.\r\n\u003E\r\n\u003E**STATEMENT:** specifica la query_id di un’istruzione da utilizzare come punto di riferimento per Time Travel.\r\n\u003E\r\n\r\n### Passaggio 4 - Fai clic su Next --\u003E\r\n\r\n## Promuovere da sviluppo a produzione\r\n\r\n### Panoramica\r\nOra che la tabella `truck_dev` è tornata allo stato in cui si trovava prima della nostra istruzione di aggiornamento errata, possiamo assicurarci che la colonna venga aggiornata correttamente. Poi promuoveremo la tabella con il calcolo corretto in produzione per completare il compito che ci è stato assegnato.\r\n\r\n### Passaggio 1 - Aggiungere i valori calcolati correttamente alla colonna\r\nUtilizzando lo stesso processo di prima, esegui la prossima query, controllando attentamente di utilizzare la sottrazione invece della divisione.\r\n\r\n```\r\nUPDATE frostbyte_tasty_bytes.raw_pos.truck_dev t\r\nSET truck_age = (YEAR(CURRENT_DATE()) - t.year);\r\n```\r\n\r\n![assets/8.1.correct_update.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/8.1.correct_update.png)\r\n\r\n### Passaggio 2 - Scambiare la tabella dall’ambiente di sviluppo a quello di produzione\r\nOra che abbiamo completato tutte le operazioni in `truck_dev`, esegui le prossime due query, in cui per prima cosa assumiamo il ruolo `sysadmin`, con privilegi più elevati. Come `sysadmin`, la seconda query utilizza [ALTER TABLE… SWAP WITH](https://docs.snowflake.com/en/sql-reference/sql/alter-table) per promuovere la tabella `truck_dev` a `truck` e viceversa.\r\n\r\nAl termine riceverai il risultato `Statement executed successfully.`.\r\n\r\n``` \r\nUSE ROLE sysadmin;\r\n\r\nALTER TABLE frostbyte_tasty_bytes.raw_pos.truck_dev \r\n    SWAP WITH frostbyte_tasty_bytes.raw_pos.truck; \r\n```\r\n\r\n### Passaggio 3 - Convalidare in produzione\r\nPer verificare che il processo sia riuscito, diamo un’occhiata alla tabella di produzione `truck` per confermare che lo swap sia stato eseguito correttamente e che i risultati di `truck_age` siano validi.\r\n\r\n``` \r\nSELECT \r\n    t.truck_id, \r\n    t.year, \r\n    t.truck_age \r\nFROM frostbyte_tasty_bytes.raw_pos.truck t \r\nWHERE t.make = 'Ford';\r\n```\r\n\r\n![assets/8.3.validate_prod.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/8.3.validate_prod.png)\r\n\r\n### Passaggio 4 - Fai clic su Next --\u003E\r\n\r\n## Fare il drop e l’undrop di tabelle\r\n\r\n### Panoramica\r\nPossiamo dire ufficialmente che il nostro sviluppatore ha completato il compito che gli era stato assegnato. Ora che la colonna `truck_age` è stata creata e calcolata correttamente, il nostro `sysadmin` può eliminare la tabella superflua e consegnare il suo lavoro.\r\n\r\n### Passaggio 1 - Fare il drop di una tabella\r\nPer rimuovere la tabella dal database, esegui la prossima query, che utilizza [DROP TABLE](https://docs.snowflake.com/en/sql-reference/sql/drop-table).\r\n\r\n```\r\nDROP TABLE frostbyte_tasty_bytes.raw_pos.truck;\r\n```\r\n\r\n![assets/9.1.drop.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.1.drop.png)\r\n\r\n**Ahi ahi!** Quel set di risultati dimostra che anche il nostro `sysadmin` può fare errori. Abbiamo rimosso per errore la tabella di produzione `truck` e non la tabella di sviluppo `truck_dev`! Per fortuna, la funzionalità Time Travel di Snowflake può di nuovo venire in nostro aiuto.\r\n\r\n### Passaggio 2 - Fare l’undrop di una tabella\r\nPrima che altri sistemi possano risentirne, esegui al più presto la prossima query, che ripristinerà ([UNDROP](https://docs.snowflake.com/en/sql-reference/sql/undrop-table)) la tabella `truck` rimossa.\r\n\r\n```\r\nUNDROP TABLE frostbyte_tasty_bytes.raw_pos.truck;\r\n```\r\n\r\n![assets/9.2.undrop.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.2.undrop.png)\r\n\r\n### Passaggio 3 - Fare il drop della tabella giusta\r\nVa bene, ora completiamo ufficialmente il lavoro eseguendo l’ultima query per fare il drop della tabella corretta `truck_dev`.\r\n\r\n```\r\nDROP TABLE frostbyte_tasty_bytes.raw_pos.truck_dev;\r\n```\r\n\r\n![assets/9.3.correctdrop.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/tasty-bytes-zero-to-snowflake-transformation-it/9.3.correctdrop.png)\r\n\r\n### Passaggio 4 - Fai clic su Next --\u003E\r\n\r\n## Conclusione e fasi successive\r\n\r\n### Conclusione\r\nOttimo lavoro! Hai completato il quickstart Tasty Bytes - Da zero a Snowflake - Trasformazione. \r\n\r\nIn questo quickstart hai:\r\n- Clonato una tabella\r\n- Utilizzato la cache dei set di risultati di Snowflake\r\n- Aggiunto una colonna a una tabella\r\n- Aggiornato i dati in una colonna\r\n- Utilizzato Time Travel per il disaster recovery dei dati\r\n- Fatto lo swap, il drop e l’undrop di una tabella\r\n\r\nSe desideri ripetere questo quickstart, usa gli script di ripristino alla fine del foglio di lavoro associato.\r\n\r\n### Fasi successive\r\nPer continuare il tuo percorso nel Data Cloud Snowflake, visita il link qui sotto per vedere tutti gli altri quickstart Powered by Tasty Bytes disponibili.\r\n\r\n- ### [Quickstart Powered by Tasty Bytes](/it/developers/guides/tasty-bytes-introduction-it/)","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},":type":"snowflake-site/components/contentfragment","isDeveloperGuidesPage":false,"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-bd04a0f38b","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-4fbb7343be",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-766923c4c3","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2024-04-22",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-dfd5044a3b","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. 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