resolve duplicate entries. unnest (array[]) set of anyelement unnest( array[‘one’, ‘row’, ‘per’, ‘item’]) Transforms a one dimensional array into rows. Returns a set of anyelement, a polymorphic pseudo-type resolve duplicate entries. unnest (array[]) set of anyelement unnest( array[‘one’, ‘row’, ‘per’, ‘item’]) Transforms a one dimensional array into rows. Returns a set of anyelement, a polymorphic pseudotype expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information

resolve duplicate entries. unnest (array[]) set of anyelement unnest( array[‘one’, ‘row’, ‘per’, ‘item’]) Transforms a one dimensional array into rows. Returns a set of anyelement, a polymorphic pseudo-type resolve duplicate entries. unnest (array[]) set of anyelement unnest( array[‘one’, ‘row’, ‘per’, ‘item’]) Transforms a one dimensional array into rows. Returns a set of anyelement, a polymorphic pseudotype expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information (transaction that updated the row). In the table, changes are added, in order, to the bottom of the table. item amount xmin xmax widget 100 0 null giblet 200 1 null sprocket 300 2 null gizmo 400 3 null The xid = 4: update tbl set amount=208 where item = 'widget' xid = 5: update tbl set amount=133 where item = 'sprocket' xid = 6: update tbl set amount=16 where item = 'widget' In the next table, the bold

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information (transaction that updated the row). In the table, changes are added, in order, to the bottom of the table. item amount xmin xmax widget 100 0 null giblet 200 1 null sprocket 300 2 null gizmo 400 3 null The xid = 4: update tbl set amount=208 where item = 'widget' xid = 5: update tbl set amount=133 where item = 'sprocket' xid = 6: update tbl set amount=16 where item = 'widget' In the next table, the bold

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information (transaction that updated the row). In the table, changes are added, in order, to the bottom of the table. item amount xmin xmax widget 100 0 null giblet 200 1 null sprocket 300 2 null gizmo 400 3 null The xid = 4: update tbl set amount=208 where item = 'widget' xid = 5: update tbl set amount=133 where item = 'sprocket' xid = 6: update tbl set amount=16 where item = 'widget' In the next table, the bold

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information (transaction that updated the row). In the table, changes are added, in order, to the bottom of the table. item amount xmin xmax widget 100 0 null giblet 200 1 null sprocket 300 2 null gizmo 400 3 null The amount=208 where item = 'widget' VMware Tanzu Greenplum 6 Documentation VMware, Inc. 276 xid = 5: update tbl set amount=133 where item = 'sprocket' xid = 6: update tbl set amount=16 where item = 'widget'

个 Postgresql 实例的高效协同和并行计算，Interconnect 承载了并行 查询计划生产和 Dispatch 分发（QD）、协调节点上 QE 执行器的并 行工作、负责数据分布、Pipeline 计算、镜像复制、健康探测等等诸 多任务。 在 Greenplum 开源以前，据说一些厂商也有开发 MPP 数据库的打算， 其中最难的部分就是在 Interconnect 上遇到了障碍，可见这项技术的 Mapreuce（如 MapR 公司及国内某 知名电商的大数据平台）；而有些则直接绕开了 Mapreduce 另起 炉灶，如 Impala、hawq 采用借鉴 MPP 计算思想来做查询优化和 内存数据 Pipeline 计算，以此来提高性能。 虽然 SQL-On-Hadoop 比原始的 Mapreduce 虽然在易用上有所提 高，但在 SQL 成熟度和关系分析上目前还与 MPP 数据库有较大差 距。 上述系统，除了

● 某⼤大型跨国⾦金金 融服务公司 ● 移动应⽤用 API 分析 ● 使⽤用Madlib进⾏行行聚 类分析，建⽴立会话 识别模型和主题模 型 ● 建⽴立scoring pipeline, 对新访问 的安全性进⾏行行评估 ● 使⽤用可视化⼯工具对 结果进⾏行行更更好地呈 现 背景 2017.thegiac.com 数据源 • 数据

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information Jinja2 Stand-alone template engine JMESPath JSON Matching Expressions Joblib Python functions as pipeline jobs jsonschema JSON Schema validation Keras (RHEL/CentOS 7 only) Deep learning Keras Applications register: installed_dir - name: change install directory ownership file: path: '{{ item.path }}' owner: "{{ greenplum_admin_user }}" group: "{{ greenplum_admin_user }}"

expression and a GROUP BY clause, the Postgres Planner returned the error could not find pathkey item to sort. The error was returned when the Postgres Planner supply did not properly manage information Jinja2 Stand-alone template engine JMESPath JSON Matching Expressions Joblib Python functions as pipeline jobs jsonschema JSON Schema validation Keras (RHEL/CentOS 7 only) Deep learning Keras Applications register: installed_dir - name: change install directory ownership file: path: '{{ item.path }}' owner: "{{ greenplum_admin_user }}" group: "{{ greenplum_admin_user }}"