數據太長，無法在MySQL上的Django中列

Question

我在模型中聲明為TextField且數據庫中為LONGTEXT的列出現此錯誤，而我嘗試插入的值只有3KB長。 AFAIK LONGTEXT的理論上限為2GB，所以我不知道為什么要限制或如何解決。 有任何想法嗎？

我得到的具體異常是：

  File "C:\Projetos\iapyx\servers\itese2\views\documents.py", line 46, in create
    self._saveItem(item)

  File "C:\Projetos\iapyx\servers\itese2\views\documents.py", line 59, in _saveItem
    doc.save()

  File "C:\Python27\lib\site-packages\django\db\models\base.py", line 460, in save
    self.save_base(using=using, force_insert=force_insert, force_update=force_update)

  File "C:\Python27\lib\site-packages\django\db\models\base.py", line 553, in save_base
    result = manager._insert(values, return_id=update_pk, using=using)

  File "C:\Python27\lib\site-packages\django\db\models\manager.py", line 195, in _insert
    return insert_query(self.model, values, **kwargs)

  File "C:\Python27\lib\site-packages\django\db\models\query.py", line 1436, in insert_query
    return query.get_compiler(using=using).execute_sql(return_id)

  File "C:\Python27\lib\site-packages\django\db\models\sql\compiler.py", line 791, in execute_sql
    cursor = super(SQLInsertCompiler, self).execute_sql(None)

  File "C:\Python27\lib\site-packages\django\db\models\sql\compiler.py", line 735, in execute_sql
    cursor.execute(sql, params)

  File "C:\Python27\lib\site-packages\django\db\backends\util.py", line 34, in execute
    return self.cursor.execute(sql, params)

  File "C:\Python27\lib\site-packages\django\db\backends\mysql\base.py", line 89, in execute
    return self.cursor.execute(query, args)

  File "C:\Python27\lib\site-packages\MySQLdb\cursors.py", line 174, in execute
    self.errorhandler(self, exc, value)

  File "C:\Python27\lib\site-packages\MySQLdb\connections.py", line 36, in defaulterrorhandler
    raise errorclass, errorvalue 

   DatabaseError: (1406, "Data too long for column 'text' at row 1")

這是導致錯誤的內容示例：

But is this the case across nations? Does increasing creativity necessarily lead to increased economic inequality? To get at this, we examine the relationship between the GCI and a standard measure of income inequality—the Gini Index. Exhibit 19 shows the relationships between income inequality and the GCI overall as well as each of the 3 T indices that comprise it. While this may come as a surprise for those familiar with the case of the United States, we find that the GCI is in fact systematically associated with lower levels of socio-economic inequality—and hence greater equality—across the nations of the world. Each and every one of the correlations between the GCI and the Gini is negative. The correlation between inequality and the overall GCI is −0.43. The Gini is also quite negatively associated with Technology (− 0.47) and Talent (−0.52) but much less so with Tolerance (− 0.06 and not statistically significant). This last is a bit surprising as one might expect more tolerant societies to be more equal on balance. That said, we believe the overall finding of a negative association between creativity and inequality to be an important one, for it implies that the general trajectory of economic development is associated with lower levels of inequality. Exhibit 20 is a scatter-graph which plots the association between the Gini measure of income inequality and the GCI for the nations of the world. The fit is not especially good and there are lots of countries above and below the line. This suggests that there are two distinctive paths for high creativity countries. On the one hand, there are countries like the United States, the United Kingdom, Singapore, and to a lesser extent, Australia and New Zealand, where high levels of creativity, productivity and economic competitiveness go hand in hand with higher levels of inequality. But there are also a substantial number of countries where high levels of creativity, competitiveness and productivity combine with much lower low levels of inequality. These are largely Scandinavian and Northern

European countries, including Sweden, Denmark, Finland, Norway, the Netherlands, and Germany. Japan is represented as well. Among the less developed nations, we find high levels of inequality in South American nations like Paraguay, Bolivia, Panama, Brazil, Honduras, Ecuador, and Argentina. Of the BRIC nations, China, Russia and particularily Brazil all exhibit much higher levels of inequality than their GCI scores would predict. There appears to be two distinct paths available to high creative development: for every high-creativity, high-inequality nation there is a high-creativity, low-inequality counterpart. This is a likely reflection of these countries’ differing levels of social welfare. Though more systematic study is needed before we can draw any firm conclusions, this finding gives us reason for optimism; at the same time, it suggests that sustainable, long-term prosperity requires a significant investment in education and skill development. This is the topic to which we now turn.

The GCI and Human Development
What is the connection between creativity and human development? To get at this, we explore the association between the GCI and the United Nations’ Human Development Index [27]. “People often value achievements that do not show up at all, or not immediately,

The GCI and inequality (correlations)

Exhibit 19

Talent

Tolerance

Technology

Global Creativity Index

−0.6

−0.4

−0.2

0.0

Correlation with Income Inequality

22 | Creativity and Prosperity: The 2010 Global Creativity Index

注意，在某些數字之前出現的“-”實際上是+-特殊字符，以UTF-8編碼

Answer 1

確保您的數據實際上是UTF8編碼的。 專欄真的是utf8嗎？

如果不是，MySQL可能會引發此錯誤。 您可以通過執行INSERT IGNORE語句並查看插入到數據庫中的內容來對此進行測試。

您可以檢查表，列和數據庫的information_schema ，以查看是否為這種情況。