New structure for delete sub predicate.
Delete sub predicate uses a string type condition_str to stored temporarily now and fields will be extracted from it using std::regex, which may introduces stack overflow when matching a extremely large string(bug of libc).
Now we attempt to use a new PB structure to hold the delete sub predicate, to avoid that problem.
message DeleteSubPredicatePB {
optional int32 column_unique_id = 1;
optional string column_name = 2;
optional string op = 3;
optional string cond_value = 4;
}
Currently, 2 versions of sub predicate will both be filled. For query, we use the v2, and during compaction we still use v1. The old rowset meta with delete predicates which had sub predicate v1 will be attempted to convert to v2 when read from PB. Moreover, efforts will be made to rewrite these meta with the new delete sub predicate.
Make preparation to use column unique id to specify a column globally.
Using the column unique id rather than the column name to identify a column is vital for flexible schema change. The rewritten delete predicate will attach column unique id.
Here we will calculate all the rowsets delete bitmaps which are committed but not published to reduce the calculation pressure of publish phase.
Step1: collect this tablet's all committed rowsets' delete bitmaps.
Step2: calculate all rowsets' delete bitmaps which are published during compaction.
Step3: write back updated delete bitmap and tablet info.
If a query hits a materialized view that has row storage enabled, but the row storage column is not present in the materialized view, it will result in a query crash. Therefore, it is necessary to include the row storage column when creating the materialized view, and serialize the row storage column during the execution of SchemaChange.
/home/zcp/repo_center/doris_master/doris/be/src/olap/rowset/segment_v2/column_reader.cpp:895:21: runtime error: load of value 423208544, which is not a valid value for type 'doris::ReaderType'
/home/zcp/repo_center/doris_master/doris/be/src/vec/columns/column_decimal.cpp:260:33: runtime error: load of misaligned address 0x7fa3348b301c for type 'int64_t' (aka 'long'), which requires 8 byte alignment
/home/zcp/repo_center/doris_master/doris/be/src/olap/block_column_predicate.cpp:82:24: runtime error: variable length array bound evaluates to non-positive value 0
/home/zcp/repo_center/doris_master/doris/be/src/vec/columns/column_string.h:225:26: runtime error: null pointer passed as argument 2, which is declared to never be null
Currently, there are some useless includes in the codebase. We can use a tool named include-what-you-use to optimize these includes. By using a strict include-what-you-use policy, we can get lots of benefits from it.
Due to concurrent load, there may be duplication in the delete bitmap of historical data and incremental calculations, resulting in duplicate calculations of missed rows.
During concurrent import, the same row location may be marked delete multiple times by different versions of rowset.
Duplicate row location need to be removed.
MoW will mark all duplicate primary key as deleted, so we can add a DCHECK while compaction, if MoW's delete bitmap works incorrectly, we're able to detect this kind of issue ASAP.
In Debug version, DCHECK will make BE crush, in release version, compaction will fail and finally load will fail due to -235
MoW updates the delete bitmap of the imported data during the compaction by rowid conversion. The correctness of rowid conversion is very important to the result of delete bitmap. So I add a rowid conversion result check.
