postgresql

问题 Closed . This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 3 months ago . Improve this question I have created table name as d with ID column as primary key and then just inserted records as shown in output, but after fetching all records this output still displayed same as order in which records are inserted. but output as a see now not in ordered form. 回答1: PostgreSQL

问题 The oracle last_day function return the last day of the month. example: nls_date_format='YYYY-MM-DD H24:MI:SS' select last_day(sysdate) from dual; LAST_DAY(SYSDATE) ------------------- 2014-06-30 15:45:43 oracle return the time value as well. I have tried below sql in PostgreSQL which return the last day of month but time value is "00:00:00". select (date_trunc('month', now()) + interval '1 month -1 day')::timestamp(0); ?column? --------------------------- 2014-06-30 00:00:00 (1 row) the sql

问题 I use Spring Boot and Data Rest to create a simple microservice in Java8 and get a postgres exception. My entity: @Entity public class ArchivedInvoice implements Serializable { ... @Column private String invoiceNumber; @Column private java.sql.Date invoiceDate; ... } My repository interface: @RepositoryRestResource(collectionResourceRel = "archivedinvoices", path = "archivedinvoices") public interface ArchivedInvoiceRepository extends PagingAndSortingRepository < ArchivedInvoice, Long > { ...

问题 Working with a large pandas DataFrame that needs to be dumped into a PostgreSQL table. From what I've read it's not a good idea to dump all at once, (and I was locking up the db) rather use the chunksize parameter. The answers here are helpful for workflow, but I'm just asking about the value of chunksize affecting performance. In [5]: df.shape Out[5]: (24594591, 4) In [6]: df.to_sql('existing_table', con=engine, index=False, if_exists='append', chunksize=10000) Is there a recommended default

问题 Working with a large pandas DataFrame that needs to be dumped into a PostgreSQL table. From what I've read it's not a good idea to dump all at once, (and I was locking up the db) rather use the chunksize parameter. The answers here are helpful for workflow, but I'm just asking about the value of chunksize affecting performance. In [5]: df.shape Out[5]: (24594591, 4) In [6]: df.to_sql('existing_table', con=engine, index=False, if_exists='append', chunksize=10000) Is there a recommended default

问题 I have a scientific database with currently 4,300,000 records. It's a scientific database, and an API is feeding it. In june 2020, I will probably have about 100,000,000 records. This is de layout of the table 'output': ID | sensor_ID | speed | velocity | direction ----------------------------------------------------- 1 | 1 | 10 | 1 | up 2 | 2 | 12 | 2 | up 3 | 2 | 11.5 | 1.5 | down 4 | 1 | 9.5 | 0.8 | down 5 | 3 | 11 | 0.75 | up ... BTW, this is dummy data. But output is a table with 5

问题 I have a scientific database with currently 4,300,000 records. It's a scientific database, and an API is feeding it. In june 2020, I will probably have about 100,000,000 records. This is de layout of the table 'output': ID | sensor_ID | speed | velocity | direction ----------------------------------------------------- 1 | 1 | 10 | 1 | up 2 | 2 | 12 | 2 | up 3 | 2 | 11.5 | 1.5 | down 4 | 1 | 9.5 | 0.8 | down 5 | 3 | 11 | 0.75 | up ... BTW, this is dummy data. But output is a table with 5

问题 I have a scientific database with currently 4,300,000 records. It's a scientific database, and an API is feeding it. In june 2020, I will probably have about 100,000,000 records. This is de layout of the table 'output': ID | sensor_ID | speed | velocity | direction ----------------------------------------------------- 1 | 1 | 10 | 1 | up 2 | 2 | 12 | 2 | up 3 | 2 | 11.5 | 1.5 | down 4 | 1 | 9.5 | 0.8 | down 5 | 3 | 11 | 0.75 | up ... BTW, this is dummy data. But output is a table with 5

问题 I have a scientific database with currently 4,300,000 records. It's a scientific database, and an API is feeding it. In june 2020, I will probably have about 100,000,000 records. This is de layout of the table 'output': ID | sensor_ID | speed | velocity | direction ----------------------------------------------------- 1 | 1 | 10 | 1 | up 2 | 2 | 12 | 2 | up 3 | 2 | 11.5 | 1.5 | down 4 | 1 | 9.5 | 0.8 | down 5 | 3 | 11 | 0.75 | up ... BTW, this is dummy data. But output is a table with 5

问题 I have the following area "name" and "polygon" values for 10 different areas ('A',50.6373 3.0750,50.6374 3.0750,50.6374 3.0749,50.63 3.07491,50.6373 3.0750) I want to create a table in postgres DB using POSTGIS Later, I will have lan and lat values (e.g. 50.5465 3.0121) in a table to compare with the above table and pull out the area name Can you help me with the code for both creating and inserting the polygon coordinates? 回答1: I don't have enough reputation to comment you question, there is