如何编写从CSV文件导入数据并填充表的存储过程?


当前回答

我创建了一个小工具,可以超级简单地将csv文件导入PostgreSQL。它只是一个命令,它将创建和填充表,但不幸的是,目前自动创建的所有字段都使用TEXT类型:

csv2pg users.csv -d ";" -H 192.168.99.100 -U postgres -B mydatabase

该工具可以在https://github.com/eduardonunesp/csv2pg上找到

其他回答

正如Paul提到的,导入在pgAdmin中起作用:

右键单击表→导入

选择一个本地文件,格式和编码。

这是一个德文pgAdmin GUI截图:

使用DbVisualizer也可以做类似的事情(我有许可证,但不确定是否有免费版本)。

右键单击表→导入表数据…

如何将CSV文件数据导入PostgreSQL表

步骤:

Need to connect a PostgreSQL database in the terminal psql -U postgres -h localhost Need to create a database create database mydb; Need to create a user create user siva with password 'mypass'; Connect with the database \c mydb; Need to create a schema create schema trip; Need to create a table create table trip.test(VendorID int,passenger_count int,trip_distance decimal,RatecodeID int,store_and_fwd_flag varchar,PULocationID int,DOLocationID int,payment_type decimal,fare_amount decimal,extra decimal,mta_tax decimal,tip_amount decimal,tolls_amount int,improvement_surcharge decimal,total_amount ); Import csv file data to postgresql COPY trip.test(VendorID int,passenger_count int,trip_distance decimal,RatecodeID int,store_and_fwd_flag varchar,PULocationID int,DOLocationID int,payment_type decimal,fare_amount decimal,extra decimal,mta_tax decimal,tip_amount decimal,tolls_amount int,improvement_surcharge decimal,total_amount) FROM '/home/Documents/trip.csv' DELIMITER ',' CSV HEADER; Find the given table data select * from trip.test;

看看这篇短文吧。


解决方案如下:

创建你的表:

CREATE TABLE zip_codes
(ZIP char(5), LATITUDE double precision, LONGITUDE double precision,
CITY varchar, STATE char(2), COUNTY varchar, ZIP_CLASS varchar);

将数据从CSV文件复制到表中:

COPY zip_codes FROM '/path/to/csv/ZIP_CODES.txt' WITH (FORMAT csv);

这里的大多数其他解决方案都要求您提前/手动创建表。这在某些情况下可能不实用(例如,如果目标表中有很多列)。因此,下面的方法可能会派上用场。

提供你的CSV文件的路径和列数,你可以使用下面的函数来加载你的表到一个临时表,它将被命名为target_table:

假设第一行具有列名。

create or replace function data.load_csv_file
(
    target_table text,
    csv_path text,
    col_count integer
)

returns void as $$

declare

iter integer; -- dummy integer to iterate columns with
col text; -- variable to keep the column name at each iteration
col_first text; -- first column name, e.g., top left corner on a csv file or spreadsheet

begin
    create table temp_table ();

    -- add just enough number of columns
    for iter in 1..col_count
    loop
        execute format('alter table temp_table add column col_%s text;', iter);
    end loop;

    -- copy the data from csv file
    execute format('copy temp_table from %L with delimiter '','' quote ''"'' csv ', csv_path);

    iter := 1;
    col_first := (select col_1 from temp_table limit 1);

    -- update the column names based on the first row which has the column names
    for col in execute format('select unnest(string_to_array(trim(temp_table::text, ''()''), '','')) from temp_table where col_1 = %L', col_first)
    loop
        execute format('alter table temp_table rename column col_%s to %s', iter, col);
        iter := iter + 1;
    end loop;

    -- delete the columns row
    execute format('delete from temp_table where %s = %L', col_first, col_first);

    -- change the temp table name to the name given as parameter, if not blank
    if length(target_table) > 0 then
        execute format('alter table temp_table rename to %I', target_table);
    end if;

end;

$$ language plpgsql;

在Python中,你可以使用这段代码自动创建带有列名的PostgreSQL表:

import pandas, csv

from io import StringIO
from sqlalchemy import create_engine

def psql_insert_copy(table, conn, keys, data_iter):
    dbapi_conn = conn.connection
    with dbapi_conn.cursor() as cur:
        s_buf = StringIO()
        writer = csv.writer(s_buf)
        writer.writerows(data_iter)
        s_buf.seek(0)
        columns = ', '.join('"{}"'.format(k) for k in keys)
        if table.schema:
            table_name = '{}.{}'.format(table.schema, table.name)
        else:
            table_name = table.name
        sql = 'COPY {} ({}) FROM STDIN WITH CSV'.format(table_name, columns)
        cur.copy_expert(sql=sql, file=s_buf)

engine = create_engine('postgresql://user:password@localhost:5432/my_db')

df = pandas.read_csv("my.csv")
df.to_sql('my_table', engine, schema='my_schema', method=psql_insert_copy)

它的速度也相对较快。我可以在大约4分钟内导入330多万行。