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Signed-off-by: xichengliudui <1693291525@qq.com>
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xichengliudui committed Nov 18, 2019
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2 changes: 1 addition & 1 deletion doc/V3HighLevelDesign.md
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Expand Up @@ -782,7 +782,7 @@ Recapitulating what we’ve covered so far:

Once we start allowing joins and subqueries, we have a whole bunch of table aliases and relationships to deal with. We have to contend with name clashes, self-joins, as well as scoping rules. In a way, the vschema has acted as a static symbol table so far. But that’s not going to be enough any more.

The core of the symbol table will contain a map whose key will be a table alias, and the elements will be [similar to the table in vschema](https://github.com/vitessio/vitess/blob/master/go/vt/vtgate/planbuilder/schema.go#L22). However, it will also contain a column list that will be built as the query is parsed.
The core of the symbol table will contain a map whose key will be a table alias, and the elements will be [similar to the table in vschema](https://github.com/vitessio/vitess/blob/0b3de7c4a2de8daec545f040639b55a835361685/go/vt/vtgate/vindexes/vschema.go#L82). However, it will also contain a column list that will be built as the query is parsed.

### A simple example

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2 changes: 1 addition & 1 deletion doc/VitessQueues.md
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Expand Up @@ -79,7 +79,7 @@ capabilities, the usual horizontal sharding process can be used.

Queue Tables are marked in the schema by a comment, in a similar way we detect
Sequence Tables
[now](https://github.com/vitessio/vitess/blob/master/go/vt/tabletserver/table_info.go#L37).
[now](https://github.com/vitessio/vitess/blob/0b3de7c4a2de8daec545f040639b55a835361685/go/vt/vttablet/tabletserver/tabletserver.go#L138).

When a tablet becomes a master, and there are Queue tables, it creates a
QueueManager for each of them.
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2 changes: 1 addition & 1 deletion java/hadoop/src/main/java/io/vitess/hadoop/README.md
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Expand Up @@ -14,7 +14,7 @@ primary key (id)) Engine=InnoDB;

Let's say we want to write a MapReduce job that imports this table from Vitess to HDFS where each row is turned into a CSV record in HDFS.

We can use [VitessInputFormat](https://github.com/vitessio/vitess/blob/master/java/hadoop/src/main/java/io/vitess/hadoop/VitessInputFormat.java), an implementation of Hadoop's [InputFormat](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/mapred/InputFormat.html), for that. With VitessInputFormat, rows from the source table are streamed to the mapper task. Each input record has a [NullWritable](https://hadoop.apache.org/docs/r2.2.0/api/org/apache/hadoop/io/NullWritable.html) key (no key, really), and [RowWritable](https://github.com/vitessio/vitess/blob/master/java/hadoop/src/main/java/io/vitess/hadoop/RowWritable.java) as value, which is a writable implementation for the entire row's contents.
We can use [VitessInputFormat](https://github.com/vitessio/vitess/blob/master/java/hadoop/src/main/java/io/vitess/hadoop/VitessInputFormat.java), an implementation of Hadoop's [InputFormat](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/mapred/InputFormat.html), for that. With VitessInputFormat, rows from the source table are streamed to the mapper task. Each input record has a [NullWritable](https://hadoop.apache.org/docs/current/api/org/apache/hadoop/io/NullWritable.html) key (no key, really), and [RowWritable](https://github.com/vitessio/vitess/blob/master/java/hadoop/src/main/java/io/vitess/hadoop/RowWritable.java) as value, which is a writable implementation for the entire row's contents.

Here is an example implementation of our mapper, which transforms each row into a CSV Text.

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