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Franck Pachot
Franck Pachot

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๐Ÿš€ YSQL-DocDB calls with yb_debug_log_docdb_requests

YugabyteDB is a distributed SQL database:

  • distributed refers to the lower half, called DocDB - a distributed document store with support for global transactions with all ACID properties
  • SQL refers to one of the API, called YSQL, which reuses PostgreSQL.

I've detailed this in Distributed SQL Deep Dive: Inside YugabyteDBโ€™s Two-Layer Architecture but if you want to learn with hands-on lab, I guess you want to see what happens between those two layers. Here is how I do it. I'm going to verify the issue #12553 which is not an issue as it has already been optimized a long time ago.

I start a single-node lab:

docker run -d --name yb -p5433:5433 -p7000:7000      \
yugabytedb/yugabyte:latest                           \
yugabyted start --daemon false                       

docker exec -it yb ysqlsh

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I tail -f the PostgreSQL log:

\pset tuples_only on
\o .yb-tail-logs.sql
select format('tail -F %s&',pg_current_logfile());
\pset tuples_only off
\o
\! sh .yb-tail-logs.sql
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Now I'm ready to set yb_debug_log_docdb_requests and see the result on my screen but, before, let's create a demo table:

drop table if exists demo;
create table demo (a int, b int);
create index demon on demo(a asc);
insert into demo select generate_series(1,10);
select count(*) from demo;
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SeqScan

Now, I enable the logging of all requestes from YSQL to DocDB and run the same count(*):

explain (costs off, analyze) select count(*) from demo;
set yb_debug_log_docdb_requests=true;
select count(*) from demo;
set yb_debug_log_docdb_requests=false;

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I run it once without the additional logging because I don't want to see the calls to get the metadata from the yb-master. They are cached, and the the second run will show only the calls to the yb-tserver(s). It is also the occasion to show the plan, this is a Seq Scan.

The following log is displayed:

I0715 14:25:09.197710   336 pg_session.cc:240] Applying operation: { READ active: 1 read_time: { read: <invalid> local_limit
: <invalid> global_limit: <invalid> in_txn_limit: <invalid> serial_no: 0 } request: client: YQL_CLIENT_PGSQL stmt_id: 58265696 schema_version: 2 targets { tscall { opcode: 4
 operands { value { int64_value: 0 } } } } column_refs { } is_aggregate: 1 limit: 1024 return_paging_state: 1 ysql_catalog_version: 22 table_id: "000033e10000300080000000000
04016" }
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We have one call here. The number of calls is important in a distributed database because the YSQL location is where you are connected (the PostgreSQL backend) but DocDB is one of the yb-tserver(s) of your YugabyteDB cluster. This can involve some latency, so you want the minimum of roundtrips. Don't worry, our engineers do the best here.

Here the operation is a READ (it counts as 1 in the Read ops/s you see in the monitoring) and the request is YQL_CLIENT_PGSQL. YQL stands for YugabyteDB Query Language, which is a client for DocDB, and this one is from PGSQL, the PostgreSQL API, running from the PostgreSQL backend.

We recognize the table_id which I described in a previous post. Here is how I get the list of my tables adn indexes with their DocDB table_id:

yugabyte=#

select  
  '0000'||lpad(to_hex(datoid::int),4,'0')
  ||'0000'||'3000'||'8000'
  ||'00000000'||lpad(to_hex(reloid::int),4,'0') 
as uuid, datname, relname, relkind, amname, nspname  from
(select oid reloid, relname, relnamespace, relkind, relowner, relam  from pg_class) rel
natural left join (select nspname,oid relnamespace from pg_namespace) ns
natural left join (select amname,oid relam from pg_am) am
cross join (select datname,oid datoid from pg_database where datname=current_database()) dat
where nspname not in ('pg_catalog','information_schema')
order by relkind desc, 1
;

               uuid               | datname  | relname | relkind | amname | nspname
----------------------------------+----------+---------+---------+--------+---------
 000033e1000030008000000000004016 | yugabyte | demo    | r       |        | public
 000033e1000030008000000000004019 | yugabyte | demon   | i       | lsm    | public
(2 rows)
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Index Only Scan

With a range condition on the indexed column, and querying only the indexed column, I have an Index Only Scan:

explain (costs off, analyze) select a from demo where a>0;
set yb_debug_log_docdb_requests=true;
select a from demo where  a>0;
set yb_debug_log_docdb_requests=false;

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This is a range scan on the index. We can see it in the EXPLAIN, but it is clear from the call, knowing the index table_id:

I0715 14:26:26.456454   336 pg_session.cc:240] Applying operation: { READ active: 1 read_time: { read: <invalid> local_limit: <invalid> global_limit: <invalid> in
_txn_limit: <invalid> serial_no: 0 } request: client: YQL_CLIENT_PGSQL stmt_id: 56172640 schema_version: 0 targets { column_id: 0 } targets { column_id: 1 } column_refs { id
s: 0 ids: 1 } is_forward_scan: 1 is_aggregate: 0 limit: 1024 return_paging_state: 1 ysql_catalog_version: 22 table_id: "000033e1000030008000000000004019" condition_expr { co
ndition { op: QL_OP_AND operands { condition { op: QL_OP_GREATER_THAN_EQUAL operands { column_id: 0 } operands { value { int32_value: 0 } } } } } } upper_bound { key: "~~~!"
 is_inclusive: 1 } col_refs { column_id: 0 attno: 1 } col_refs { column_id: 1 attno: -101 } partition_key: "48800000000021" }

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There is a range condition here, QL_OP_GREATER_THAN_EQUAL, with a lower bound (value { int32_value: 0 }) on the first column of the index ({ column_id: 0 }). What I wanted to verify here is that there is only one call.

Index Scan

By selecting all columns, it is to read the table in addition to the index:

explain (costs off, analyze) select * from demo where a>0;
set yb_debug_log_docdb_requests=true;
select * from demo where  a>0;
set yb_debug_log_docdb_requests=false;
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I have two calls to DocDB:

I0715 14:27:36.410634   336 pg_session.cc:240] Applying operation: { READ active: 1 read_time: { read: <invalid> local_limit: <invalid> global_limit: <invalid> in
_txn_limit: <invalid> serial_no: 0 } request: client: YQL_CLIENT_PGSQL stmt_id: 58462304 schema_version: 0 targets { column_id: 1 } column_refs { ids: 1 } is_forward_scan: 1
 is_aggregate: 0 limit: 1024 return_paging_state: 1 table_id: "000033e1000030008000000000004019" condition_expr { condition { op: QL_OP_AND operands { condition { op: QL_OP_
GREATER_THAN_EQUAL operands { column_id: 0 } operands { value { int32_value: 0 } } } } } } upper_bound { key: "~~~!" is_inclusive: 1 } col_refs { column_id: 1 attno: -101 }
partition_key: "48800000000021" }

I0715 14:27:36.411345   336 pg_session.cc:240] Applying operation: { READ active: 1 read_time: { read: <invalid> local_limit: <invalid> global_limit: <invalid> in_txn_limit:
 <invalid> serial_no: 0 } request: client: YQL_CLIENT_PGSQL stmt_id: 56172640 schema_version: 2 targets { column_id: 1 } targets { column_id: 2 } targets { column_id: -8 } c
olumn_refs { ids: 1 ids: 2 } is_forward_scan: 1 is_aggregate: 0 limit: 1024 return_paging_state: 1 ysql_catalog_version: 22 table_id: "000033e1000030008000000000004016" ybct
id_column_value { value { binary_value: "47DC00532F3E68ABEAA545879804CD13CF0C340E00002121" } } batch_arguments { order: 0 ybctid { value { binary_value: "47DC00532F3E68ABEAA
545879804CD13CF0C340E00002121" } } } batch_arguments { order: 1 ybctid { value { binary_value: "475DF9530C646C9C79FE4B1C84AC32D590FF102600002121" } } } batch_arguments { ord
er: 2 ybctid { value { binary_value: "47DDFD53A6B8D58EFAE94FFD9FC1CBD136BDBBAF00002121" } } } batch_arguments { order: 3 ybctid { value { binary_value: "4758C053A4D995B0370B
4C9FB1E97520A0992C6A00002121" } } } batch_arguments { order: 4 ybctid { value { binary_value: "4792BC536CA73C978AE34FD1A1A1432B278DC18B00002121" } } } batch_arguments { orde
r: 5 ybctid { value { binary_value: "472C1253F1CD65ABE9C64B8380E8DCF1B2FC67D400002121" } } } batch_arguments { order: 6 ybctid { value { binary_value: "470EAB53DB8CD72BFC014
44CA2E88A04287B938300002121" } } } batch_arguments { order: 7 ybctid { value { binary_value: "479B3E53BA1156DB6C9C4AF09C7352C17B8ECDDC00002121" } } } batch_arguments { order
: 8 ybctid { value { binary_value: "47786553B15A4CA138624D70824263AAE1AAE71600002121" } } } batch_arguments { order: 9 ybctid { value { binary_value: "47341353692414BBF3934B
468B103C2153519D3200002121" } } } col_refs { column_id: 1 attno: 1 } col_refs { column_id: 2 attno: 2 } partition_key: "DC00" }
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In addition to the request to the index, similar to the previous one, but returning the primary key of the table, I see one call to get the additional columns from the table. I can see that the 10 primary key have been grouped as 10 batch_arguments. So that's what I wanted to verify. In YugabyteDB secondary indexes global, consistent, and high performance.

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