python - 如何从 SQL 表中下载大数据并通过一次获取 1000 条左右的记录连续保存到 csv 中

Question

我有一个包含 1000 万行和很多列的 SQL 表，查询时表大小约为 44 GB。

但是我试图从此表中仅获取 3 列并将其保存到 csv/加载到数据帧中，python 会永远运行。 即

 pd.read_sql("select a,b,c from table") is taking more than 1 hour and not returning data

How to achieve this? Can I load this entire data in dataframe at once is that a viable option.
After this I should be able to perform some data manipulations on these rows.

2. OR should I download this to csv and read this data part by part to in-memory.

If its 2. How to code for 2?

Code tried for 2 so far is :

   def iter_row(cursor, size=10):
while True:
    rows = cursor.fetchmany(size)
    if not rows:
        break
    for row in rows:
        yield row

  def query_with_fetchmany():

    cursor.execute("SELECT * FROM books")

    for row in iter_row(cursor, 10):
        print(row)
    cursor.close()

Answer 1

您可以分块读取数据:

for c in pd.read_sql("select a,b,c from table", con=connection, chunksize=10**5):
    c.to_csv(r'/path/to/file.csv', index=False, mode='a')