Hanacolumnstoredialect Does Not Support Identity Key Generation

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Find more on Hibernate: Dialect does not support identity key generation Or get search suggestion and latest updates. Related Topics: Hibernate DDL Generation; Auto generated primary key in hibernate? Hibernate mapping many to many ewlationships hibernate; problem: I've done this in ACCESS, but not.
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Oracle dialect does not support identity key generation 576227 Nov 19, 2012 4:28 PM Hello, I'm trying to run an integration tests suite against an Oracle 10g XE database server on a Linux box.
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Hanacolumnstoredialect Does Not Support Identity Key Generation Work
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Hanacolumnstoredialect Does Not Support Identity Key Generation Work
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Hanacolumnstoredialect Does Not Support Identity Key Generation Mean
Hanacolumnstoredialect Does Not Support Identity Key Generation Mean

Aug 04, 2017 IDENTITY column generation is not possible with ROW store tables. Importing data from CSV/Control file is possible only when the column is created with GENERATED BY DEFAULT. To import data for GENERATED ALWAYS column, the column should not be a primary key and should accept NULL values. Examining the IDENTITY feature.

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Where clauses are another difficult area to compare Hana with relational databases. What should we compare? An index column in Hana and RDBMS? Non-indexed columns? Indexed in the RDBMS but not indexed in Hana? Actually, as the theme throughout this test is the best case for RDBMSes and the worst for Hana we will do just that.

Difference between Hana and RDBMSes for this use case

Compression: As Hana has to uncompress the data for the selected columns, more CPU power is needed as with an RDBMS where the data is just read as is.
Compression: Because of the way Hana does the compression finding all rows with a matching value is fast.
Pre-Built Index: If the RDBMS has no index on the column all it can do is a full table scan reading the entire table - all rows, all columns - and then take one the rows matching our where clause. The only way to speed that up is using small tables or index each column.

What number to expect from a traditional database

A full table scan we know already takes at least 300 seconds if all is on disk or 4 seconds when all is cached.
Having the column index is not a guarantee that the query will run faster in an RDBMS, it depends on the data distribution. Imagine a primary key index: There walking through the tree to find the one row with the matching value is a matter of 1ms. But in the other extreme, when all values of this column would be identical, so the where clause would return all rows anyhow, reading the index just to get a list with all individual rows and reading each row based on that list from the table would certainly take longer than just reading the entire table. The border commonly used is, if the where clause is expected to find less than 25% of the entire table data, only then use the index. Some databases provide bitmap indexes as another type more suited for that but then you again have to decide what index to use upfront etc.
Anyway, in Hana such a query against a non-indexed column should take less than a second. That is what I expect from it even if that is much better than what a RDBMS can achieve in an equal case.

Result

The way the compression works in Hana is two staged, first for a column a list of distinct values is created and then the pointer to the rows are compressed. So in my case I have distinct values for partition ID between 0 and 30, my where clause is partition_id=4, so Hana will read from the list of values the key code of this entry. Okay, as the integer is a small number already there is not much gained from this level of compression. But imagine we would select on a column that has 30 distinct values and each are 100 char text long. Then the RDBMS would have 30 million times 100 characters in the table, Hana would have 30 entries with the 100 char text plus a single byte as key for each text, in the 30 million row table it would store the single byte key only.
Yet another benefit we did not get with this test case, perfect just what I wanted.
Now the 30 million keys are compressed, maybe like 'Oh, the next 500 entries are all of key 4'. So finding all rows with key 4 is relatively easy now. And the performance test shows that: 0.3 seconds

Please note, I never said that Hana does not support indexes. For primary key columns an index might still make sense. All I said was that due to the columnar orientation and the compression even large tables can have a where clause on columns.

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我删除了一部分数据：

mysql> delete from pending_22 limit 1000;
Query OK, 1000 rows affected (2.99 sec)

但是delete是不会自动释放空间的，该表表空间大小仍然是之前的大小：30408704

想通过optimize table来释放下空间：

mysql> optimize table pending_22;

+------------------+----------+----------+-------------------------------------------------------------------+
Table Op Msg_type Msg_text
+------------------+----------+----------+-------------------------------------------------------------------+