{"id":143994,"date":"2025-09-22T17:11:59","date_gmt":"2025-09-22T15:11:59","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/reliz-subd-duckdb-1-4-0-s-podderzhkoj-shifrovaniya-bd"},"modified":"2025-09-22T17:11:59","modified_gmt":"2025-09-22T15:11:59","slug":"reliz-subd-duckdb-1-4-0-s-podderzhkoj-shifrovaniya-bd","status":"publish","type":"post","link":"https:\/\/prohoster.info\/it\/blog\/novosti-interneta\/reliz-subd-duckdb-1-4-0-s-podderzhkoj-shifrovaniya-bd","title":{"rendered":"Rilascio del DBMS DuckDB 1.4.0 con supporto per la crittografia del database","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>\u00c8 stata pubblicata la versione 1.4.0 del database DuckDB, progettato per l'esecuzione di query analitiche e concettualmente simile a SQLite. DuckDB combina propriet\u00e0 di SQLite come compattezza, integrazione come libreria, archiviazione del database in un unico file e interfaccia a riga di comando, con funzionalit\u00e0 e ottimizzazioni per eseguire query analitiche che coinvolgono una parte significativa dei dati memorizzati, ad esempio, eseguendo l'aggregazione di tutto il contenuto delle tabelle o la fusione di pi\u00f9 tabelle di grandi dimensioni. Il codice del progetto \u00e8 scritto in C++ e distribuito sotto licenza MIT.     <\/p>\n<p>DuckDB offre un dialetto esteso del linguaggio SQL, che include funzionalit\u00e0 aggiuntive per la gestione di query molto complesse e prolungate. Supporta tipi complessi (array, strutture, unioni) e consente l'esecuzione di sottoquery correlate arbitrari e nidificate. \u00c8 possibile eseguire pi\u00f9 query simultaneamente e inviare query direttamente da file nei formati CSV e Parquet. \u00c8 supportato l'import di dati da database PostgreSQL.    <\/p>\n<p>Il progetto utilizza un'interfaccia basata su SQLite, un parser di PostgreSQL, il componente Date Math di MonetDB, la propria implementazione delle funzioni di finestra (basata sull'algoritmo Segment Tree Aggregation), un gestore delle espressioni regolari basato sulla libreria RE2, ottimizzatore delle query personalizzato, meccanismo MVCC per la gestione della concorrenza (Multi-Version Concurrency Control), e un motore di esecuzione delle query vettorizzato basato sull'algoritmo Hyper-Pipelining Query Execution, che consente di elaborare grandi set di valori con un'unica operazione.    <\/p>\n<p>Nella nuova versione:  <\/p>\n<ul>\n<li class=\"l\"> \u00c8 stata aggiunta la supporto per la memorizzazione dei file di database in forma crittografata. Per la crittografia viene utilizzato l'algoritmo AES-256 in modalit\u00e0 GCM. Non solo il file principale con i dati viene crittografato, ma anche i log WAL e i file temporanei. Le chiavi per la crittografia del database vengono impostate con il comando ATTACH tramite il parametro ENCRYPTION_KEY.         ATTACH 'encrypted.db' AS enc_db (ENCRYPTION_KEY 'quack_quack');\n<li class=\"l\"> \u00c8 stata aggiunta la supporto per il comando \u00abMERGE INTO\u00bb, che pu\u00f2 essere utilizzato come alternativa all'espressione \u00abINSERT ... ON CONFLICT\u00bb, non richiedendo una chiave primaria e funzionando con condizioni di fusione arbitrarie. Il comando \u00abMERGE INTO\u00bb consente di creare espressioni SQL condizionali, combinando in un'unica espressione le operazioni INSERT, UPDATE e DELETE. Ad esempio, utilizzando MERGE, \u00e8 possibile organizzare la fusione di due tabelle, inserendo le registrazioni mancanti e aggiornando quelle esistenti.        WITH deletes(item_id, delete_threshold) AS (VALUES (10, 3000))         MERGE INTO Stock             USING deletes USING (item_id)         WHEN MATCHED AND balance &lt; delete_threshold             THEN DELETE         RETURNING merge_action, *;        \n\n<li class=\"l\"> In aggiunta, per lavorare con tabelle nel formato Apache Iceberg, \u00e8 stata aggiunta la supporto per operazioni di scrittura (in precedenza era supportata solo la lettura), il che consente di trasferire dati da Iceberg a DuckDB e viceversa.\n<li class=\"l\"> Nel client della riga di comando \u00e8 stato aggiunto un indicatore di progresso per l'esecuzione dell'operazione con una previsione del tempo rimanente fino al completamento.\n<li class=\"l\"> \u00c8 stata aggiunta la funzione finestra \u00abFILL\u00bb, che pu\u00f2 essere utilizzata per interpolare valori mancanti in finestre ordinate.         FROM (VALUES (1, 1), (2, NULL), (3, 42)) t(c1, c2)     SELECT fill(c2) OVER (ORDER BY c1) f;     1      21     42\n<li class=\"l\"> \u00c8 stato implementato il componente aggiuntivo Teradata Connector per la connessione ai database Teradata. Il componente consente di manipolare tabelle, eseguire query e lanciare comandi SQL direttamente in Teradata, utilizzando DuckDB.\n<li class=\"l\"> \u00c8 stata aggiunta la supporto per il checkpoint delle tabelle memorizzate in memoria, il che ha reso possibile implementare la supporto per la compressione. Inoltre, durante il checkpoint viene eseguita la pulizia delle righe eliminate e il rilascio di spazio dopo le operazioni di eliminazione.       ATTACH ':memory:' AS memory_compressed (COMPRESS);\n<li class=\"l\"> Sono state proposte diverse ottimizzazioni delle prestazioni: l'implementazione dell'ordinamento \u00e8 stata trasferita all'uso dell'algoritmo di fusione k-way, che riduce il movimento dei dati. Le espressioni di tabella comuni (Common Table Expression, CTE) ora vengono materializzate per impostazione predefinita.          <\/ul>\n<p>Fonte: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=63922\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d \u0432\u044b\u043f\u0443\u0441\u043a \u0421\u0423\u0411\u0414 DuckDB 1.4.0, \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0438 \u043a\u043e\u043d\u0446\u0435\u043f\u0442\u0443\u0430\u043b\u044c\u043d\u043e \u043d\u0430\u043f\u043e\u043c\u0438\u043d\u0430\u044e\u0449\u0435\u0439 SQLite. 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