Apache Kyuubi 1.7.0 Documentation
cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 400 页 | 5.25 MB | 1 年前3Apache Kyuubi 1.7.0-rc1 Documentation
cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 400 页 | 5.25 MB | 1 年前3Apache Kyuubi 1.7.0-rc0 Documentation
cloud storage or an on-prem HDFS cluster. Lakehouse formation and analytics Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. Logical data warehouse Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 404 页 | 5.25 MB | 1 年前3Apache Kyuubi 1.7.0-rc1 Documentation
storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | +------------+ case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 206 页 | 3.78 MB | 1 年前3Apache Kyuubi 1.7.0 Documentation
storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | +------------+ case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 206 页 | 3.78 MB | 1 年前3Apache Kyuubi 1.7.0-rc0 Documentation
storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | +------------+ case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 210 页 | 3.79 MB | 1 年前3PyFlink 1.15 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.1.2.1 QuickStart: Table API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.1.2.2 QuickStart: DataStream 26 1.3.4.1 O1: Could not find any factory for identifier ‘xxx’ that implements ‘org.apache.flink.table.factories.DynamicTableFactory’ in the classpath . . . . . . . 26 1.3.4.2 O2: ClassNotFoundException: . . . 29 1.3.4.3 O3: NoSuchMethodError: org.apache.flink.table.factories.DynamicTableFactory$Context.getCatalogTable()Lorg/apache/flink/table/catalog/CatalogTable 30 1.3.5 Runtime issues . . . . . .0 码力 | 36 页 | 266.77 KB | 1 年前3PyFlink 1.16 Documentation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.1.2.1 QuickStart: Table API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.1.2.2 QuickStart: DataStream 26 1.3.4.1 O1: Could not find any factory for identifier ‘xxx’ that implements ‘org.apache.flink.table.factories.DynamicTableFactory’ in the classpath . . . . . . . 26 1.3.4.2 O2: ClassNotFoundException: . . . 29 1.3.4.3 O3: NoSuchMethodError: org.apache.flink.table.factories.DynamicTableFactory$Context.getCatalogTable()Lorg/apache/flink/table/catalog/CatalogTable 30 1.3.5 Runtime issues . . . . . .0 码力 | 36 页 | 266.80 KB | 1 年前3Apache Kyuubi 1.7.3 Documentation
storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | +------------+ case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 211 页 | 3.79 MB | 1 年前3Apache Kyuubi 1.7.3-rc0 Documentation
storage or an on-prem HDFS cluster. • Lakehouse formation and analytics – Easily build an ACID table storage layer via Hudi, Iceberg, or/and Delta Lake. • Logical data warehouse – Provide a relational beeline console. For instance, > SHOW DATABASES; You will see a wall of operation logs, and a result table in the beeline console. omitted logs +------------+ | namespace | +------------+ | default | +------------+ case to create another connection, the engine will be reused. You may notice that the time cost for connection here is much shorter than the last round. If you use a different user to create a new connection0 码力 | 211 页 | 3.79 MB | 1 年前3
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