HBase storage engine

Data mapping from HBase to SQL

Hbase data model and operations

1.1 HBase data model

• An HBase table consists of rows, which are identified by row key.
• Each row has an arbitrary (potentially, very large) number of columns.
• Columns are split into column groups, column groups define how the columns are stored (not reading some column groups is an optimization).
• Each (row, column) combination can have multiple versions of the data, identified by timestamp.

1.2 Hbase read operations

HBase API defines two ways to read data:

• Point lookup: get record for a given row_key.

• Point scan: read all records in [startRow, stopRow) range.

Both kinds of scans allow to specify:

• A column family we're interested in
• A particular column we're interested in

The default behavior for versioned columns is to return only the most recent version. HBase API also allows to ask for

• versions of columns that were valid at some specific timestamp value;
• all versions that were valid within a specifed [minStamp, maxStamp) interval.
• N most recent versions We'll refer to the above as [VersionedDataConds].

One can see two ways to map HBase tables to SQL tables:

2. Per-row mapping

Let each row in HBase table be mapped into a row from SQL point of view:

SELECT * FROM hbase_table;

row-id column1 column2  column3  column4  ...
------ ------- -------  -------  -------  
row1    data1   data2
row2                     data3    
row3    data4                      data5

The problem is that the set of columns in a HBase table is not fixed and is potentially is very large. The solution is to put all columns into one blob column and use Dynamic Columns (http://kb.askmonty.org/en/dynamic-columns) functions to pack/extract values of individual columns:

row-id dyn_columns
------ ------------------------------
row1   {column1=data1,column2=data2}
row2   {column3=data3}
row3   {column1=data4,column4=data5}

2.2 Mapping definition

Table DDL could look like this:

CREATE TABLE hbase_tbl_rows (
  row_id BINARY(MAX_HBASE_ROWID_LEN),
  columns BLOB,
  PRIMARY KEY (row_id)
) ENGINE=hbase_row;

(TODO: Does Hbase have MAX_HBASE_ROWID_LEN limit? What is it? A: Ignore this: allow the user to define the column with arbitrary limit. Don't do operations with rows that have row_id longer than the limit)

The `columns` blob will hold values (and names) for all columns.

Access to name/value of individual columns is to be done with dynamic column functions (see http://kb.askmonty.org/en/dynamic-columns).

Functions for reading data:

  COLUMN_GET(dynamic_column, column_nr as type)
  COLUMN_EXISTS(dynamic_column, column_nr);
  COLUMN_LIST(dynamic_column);

Functions for data modification:

  COLUMN_ADD(dynamic_column, column_nr,  value [as type], ...)
  COLUMN_DELETE(dynamic_column, column_nr, column_nr, ...);

2.2.1 Required improvements in Dynamic Columns

Dynamic column functions cannot be used as-is:

• HBase columns have string names, Dynamic Columns have numbers (see column_nr parameter for the above functions). The set of column names in HBase is potentially very large, there is no way to get a list of all names: we won't be able to solve this with enum-style mapping, we'll need real support for string names.

• HBase has column families, Dynamic Columns do not . Column family is not just a ':' in the column name. For example, HBase API allows to request "all columns from within a certain column family".

• HBase supports versioned data, Dynamic Columns do not. A possible simple solution is to have global/session @@hbase_timestamp variable which will globally specify the required data version.

• (See also note below about efficient execution)

2.3 Queries in per-row mapping

# Point-select:
SELECT COLUMN_GET(hbase_tbl.columns, 'column_name' AS INTEGER)
FROM hbase_tbl
WHERE 
  row_id='hbase_row_id';


#  Range select:
#   (the example uses BETWEEN but we will support arbitrary predicates)
SELECT COLUMN_GET(hbase_tbl.columns, 'column_name' AS INTEGER)
FROM hbase_tbl
WHERE 
  row_id BETWEEN 'hbase_row_id1' AND 'hbase_row_id2';

# Update a column for a row
UPDATE hbase_tbl SET columns=COLUMN_ADD(columns, 'column_name', 'value') WHERE row_id='hbase_row_id1';

# Add a column
UPDATE hbase_tbl SET columns=COLUMN_ADD(columns, 'column_name', 'value') WHERE row_id='hbase_row_id1';

# Insert a row with a column
INSERT INTO hbase_tbl (row_id, columns) VALUES 
  ('hbase_row_id', COLUMN_CREATE('column_name', 'column-value'));

Q: It's not clear how to access versioned data? Can we go without versioned 
   data for the first milestone? 
   (and then, use global @@hbase_timestamp  for the second milestone?)

Q: It's not clear how to select "all columns from column family X".

2.4 Efficient execution for per-row mapping

The table declares:

  row_id BINARY(MAX_HBASE_ROWID_LEN),
  ...
  PRIMARY KEY (row_id)

this will allow the range/ref optimizer to construct point-lookups and range scans for row_id.

Q: will we need joins, i.e. do I need to implement Multi-Range-Read and support Batched Key Access right away?

Current MariaDB works with Dynamic Columns with this scenario:

1. When the record is read, the entire blob is read into memory
2. Dynamic Column functions operate on the in-memory data (read and update some particular columns in it)
3. [If this is an UPDATE] the entire blob is written back to the table

If we use this approach with HBase, we will end up reading lots of unneeded columns.

Solution #1: on-demand reads

• When table record is read, don't read any columns, return a blob handle.
• Dynamic Column functions will use the handle to read particular columns. The column is read from HBase only when its value is requested.

This scheme ensures there are no redundant data reads, at the cost making extra mysqld<->HBase roundtrips (which are likely to be expensive)

Solution #2: List of reads

• Walk through the query and find all references to hbase_table.columns.
• Collect the names of columns that are read, and retrieve only these columns.

This may cause redundant data reads, for example for

  SELECT COLUMN_GET(hbase_tbl, 'column1' AS INTEGER) 
  FROM hbase_tbl
  WHERE 
    row_id BETWEEN 'hbase_row_id1' AND 'hbase_row_id2' AND 
    COLUMN_GET(hbase_tbl, 'column2' AS INTEGER)=1

column1 will be read for rows which have column2!=1. This still seems to be better than making extra roundtrips.

There is a question of what should be done when the query has references like

  
  COLUMN_GET(hbase_tbl, {non-const-item} AS ...) 

where it is not possible to tell in advance which columns must be read. Possible approaches are

• retrieve all columns
• fetch columns on demand
• stop the query with an error.

Further details

See hbase-per-row-mapping-efficient-execution.

3. Per-cell mapping

HBase shell has 'scan' command, here's an example of its output:

hbase(main):007:0> scan 'testtable'
 ROW COLUMN+CELL
  myrow-1 column=colfam1:q1, timestamp=1297345476469, value=value-1
  myrow-2 column=colfam1:q2, timestamp=1297345495663, value=value-2
  myrow-2 column=colfam1:q3, timestamp=1297345508999, value=value-3

Here, one HBase row produces multiple rows in the query output. Each output row represents one (row_id, column) combination, so rows with multiple columns (and multiple revisions of column data) can be easily represented.

3.1 Table definition

Mapping could be defined as follows:

CREATE TABLE hbase_tbl_cells (
  row_id binary(MAX_HBASE_ROWID_LEN),
  column_family binary(MAX_HBASE_COLFAM_LEN),
  column_name binary(MAX_HBASE_NAME_LEN),
  timestamp TIMESTAMP,
  value BLOB,
  PRIMARY KEY (row_id, column_family, column_name, timestamp)
) ENGINE=hbase_cell;

There is no need for dynamic columns in this mapping.

• NOTE: It is nice to have SQL table DDLs independent of the content of the backend hbase table. This saves us from the need to synchronize table DDLs between hbase and mysql (NDB cluster had to do this and they have ended up implementing a very complex system to do this).

3.2 Queries in per-cell mapping

# Point-select:
SELECT value 
FROM hbase_cell
WHERE 
  row_id='hbase_row_id' AND 
  column_family='hbase_column_family' AND column_name='hbase_column'
  ...

#  Range select:
#   (the example uses BETWEEN but we will support arbitrary predicates)
SELECT value 
FROM hbase_cell
WHERE 
  row_id BETWEEN 'hbase_row_id1' AND 'hbase_row_id2' AND 
  column_family='hbase_column_family' AND column_name='hbase_column'


# Update a column
UPDATE hbase_cell SET value='value' 
WHERE row_id='hbase_row' AND 
      column_family='col_family' AND column_name='col_name'


# Add a column (this will add a row if one doesn't exist yet)
INSERT INTO hbase_cell values ('hbase_row', 'col_family','col_name','value');

Note that

• accessing versioned data is easy: one can read some particular version, versions within a date range, etc
• it is also easy to select all columns from a certain column family.

3.3 Mapping of operations on the data

Mapping for SELECT

The table is defined as having a

  PRIMARY KEY (row_id, column_family, column_name, timestamp)

which allows to make use of range optimizer to get ranges on

• rowid
• rowid, column_family
• rowid, column_family, column_name
• ...

If a range specifies one row, we can read it with HTable.get(), otherwise we'll have to use HTable.getScanner() and make use of the obtained scanner.

Multiple non-equality conditions

HBase API allows to scan a range of rows, retrieving only certain column name or certain column families. In our SQL mapping, this can be written as:

SELECT value
FROM hbase_cell
WHERE
  row_id BETWEEN 'hbase_row_id1' AND 'hbase_row_id2' AND
  column_family='hbase_column_family'                           (*)

If we feed this into the range optimizer, it will produce a range:

  ('hbase_row_id1', 'hbase_column_family') <= (row_id, column_family) <=
  ('hbase_row_id2', 'hbase_column_family')

which includes all column families for records which satisfy

  'hbase_row_id1' < rowid < 'hbase_row_id2'

This will cause extra data to be read.

Possible solutions:

• Extend multi-range-read interface to walk the 'SEL_ARG graph' instead of list of ranges. This will allow to capture the exact form of conditions like (*).
• Implement table condition pushdown and and perform independent condition analysis.
• Define more indexes, so that ranges are "dense". ^{what about (row_id BETWEEN $X AND $Y) AND (timestamp BETWEEN $T1 AND $T2) ? No matter which index you define, the range list will not be identical to the WHERE clause.}

Mapping for INSERT

INSERT will be translated into HTable.checkAndPut(..., value=NULL) call. That way, attempt to insert a {rowid, column} that already exists will fail.

Mapping for DELETE

MySQL/MariaDB's storage engine API handles DELETEs like this:

• Use some way to read the record that should be deleted
• call handler->ha_delete_row(). It will delete the row that was last read.

ha_hbase_cell can remember {rowid, column_name} of the record, and then use HBase.checkAndDelete() call, so that we're sure we're deleting what we've read.

If we get a statement in form of {{ DELETE FROM hbase_cell WHERE rowid='habase_row_id' AND column_family='...' AND column_name='...'; }} then reading the record is redundant (we could just make one HBase.checkAndDelete()). This will require some form of query pushdown, though.

Mapping for UPDATE

UPDATEs are similar to deletes as long as row_id, column_family, and column_name fields are not changed (that is, only column_value changes). Like with DELETEs:

• HBase.checkAndPut() call can be used to make sure we're updating what we've read
• one-point UPDATEs may need a shortcut so that we don't have to read the value before we make an update.

If UPDATE statement changes row_id, column_family, or column_name field, it becomes totally different. HBase doesn't allow to change rowid of a record. We can only remove the record with old rowid, and insert a record with the new rowid. HBase doesn't support multi-row transactions, so we'll want to insert the new variant of the record before we have deleted the old one (I assume that data duplication is better than data loss).

For first milestone, we could disallow UPDATEs that change row_id, column_family or column_name.

4. Select-columns mapping

This is a simplification of the per-row mapping. Suppose, the user is only interested in particular columns with names `column1` and `column2`. They create a table with this definition:

CREATE TABLE hbase_tbl_cells (
  row_id binary(MAX_HBASE_ROWID_LEN),
  column1  TYPE,
  column2  TYPE,
  PRIMARY KEY (row_id),
  KEY(column1),
  KEY(column2)
) ENGINE=hbase_columns;

and then access it. Access is done like in per-row mapping, but without use of dynamic columns.

This mapping imposes lots of restrictions: it is only possible to select a fixed set of columns, there is no way to specify version of the data, etc.

5. Comparison of the mappings

If we select two columns from a certain row, per-cell mapping produces "vertical" result, while per-row mapping produces "horizontal" result.

# Per-cell:
SELECT column_name, value 
FROM hbase_cell
WHERE 
  row_id='hbase_row_id1' AND 
  column_family='col_fam' AND column_name IN ('column1','column2')
+-------------+-------+
| column_name | value |
+-------------+-------+
| column1     | val1  |
| column2     | val2  |
+-------------+-------+

# Per row:
SELECT 
  COLUMN_GET(columns, 'col_fam:column1') as column1,  
  COLUMN_GET(columns, 'col_fam:column2') as column2,
FROM hbase_row
WHERE 
  row_id='hbase_row_id1' 
+---------+---------+
| column1 | column2 |
+---------+---------+
| val1    | val2    |
+---------+---------+

Per-cell mapping:

• Allows a finer control over selection of versioned data (easy to specify [range of] versions to select), column families, etc.
• Is more suitable for cases when one needs to select an arbitrarily-long list of columns.

Per-row mapping:

• is easier to use when one is selecting a pre-defined set of columns
• allows joins that involve multiple columns (in per-cell mapping, one needs to do an [inefficient?] self-join if they want to do a join between rows in an hbase table and something else).

6. Interfacing with HBase

HBase is in Java, and its native client API is a java library. We need to interface with it from C++ storage engine code. Possible options are:

6.1 Use Thrift

This requires HBase installation to run a Thrift server

6.2 Re-implement HBase's network protocol

• It seems to be a custom-made RPC protocol.
• There is an independent re-implementation here: https://github.com/stumbleupon/asynchbase. It is 10K lines of Java code, which gives an idea about HBase's protocol complexity
  • It seems to support only a subset of features? I.e. I was unable to find mention of pushed down conditions support?
  • Look in HBaseRpc.java for "Unofficial Hadoop / HBase RPC protocol documentation"

6.3 Use JNI+HBase client protocol

• not sure how complex this is
• Mark has mentioned this has an unacceptable overhead?

7. Consistency, transactions, etc

• HBase has single-record transactions. Does this mean that HBase storage engine will have MyISAM-like characteristics? e.g. if we fail in the middle of a multi-row UPDATE, there is no way to go back.

• Q: Are the writes important at all? (e.g. if we've had the first version with provide read-only access, would that be useful?) A: Yes?