![JSON Function Examples
SELECT JSON_ARRAY(56, 3.1416, 'My name is "Foo"', NULL);
+--------------------------------------------------+
| Json_Array(56, 3.1416, 'My name is "Foo"', NULL) |
+--------------------------------------------------+
| [56, 3.1416, "My name is "Foo"", null] |
+--------------------------------------------------+
SELECT JSON_OBJECT("id", 1, "name", "Monty");
+---------------------------------------+
| JSON_OBJECT("id", 1, "name", "Monty") |
+---------------------------------------+
| {"id": 1, "name": "Monty"} |
+---------------------------------------+
JSON array from
listed values
JSON object from
key,value pairs](https://image.slidesharecdn.com/022017emearoadshowmilan-whatsnew-mariadbserver102andmaxscale21-170511204624/85/03-2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale-2_1-19-320.jpg)
![JSON Function Examples
SELECT json_query('{"key1":123, "key1": [1,2,3]}',
'$.key1');
+-------------------------------------------------------+
| json_query('{"key1":123, "key1": [1,2,3]}', '$.key1') |
+-------------------------------------------------------+
| [1,2,3] |
+-------------------------------------------------------+
select json_query('{"key1":{"a":1, "b":[1,2]}}', '$.key1');
+-----------------------------------------------------+
| json_query('{"key1":{"a":1, "b":[1,2]}}', '$.key1') |
+-----------------------------------------------------+
| {"a":1, "b":[1,2]} |
+-----------------------------------------------------+
query JSON array
query JSON object](https://image.slidesharecdn.com/022017emearoadshowmilan-whatsnew-mariadbserver102andmaxscale21-170511204624/85/03-2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale-2_1-20-320.jpg)
![JSON Function
Examples
SELECT ST_AsGeoJSON(ST_GeomFromText('POINT(5.3 7.2)'));
+-------------------------------------------------+
| ST_AsGeoJSON(ST_GeomFromText('POINT(5.3 7.2)')) |
+-------------------------------------------------+
| {"type": "Point", "coordinates": [5.3, 7.2]} |
+-------------------------------------------------+
SET @j = '{ "type": "Point", "coordinates": [5.3, 15.0]}';
SELECT ST_AsText(ST_GeomFromGeoJSON(@j));
+-----------------------------------+
| ST_AsText(ST_GeomFromGeoJSON(@j)) |
+-----------------------------------+
| POINT(5.3 15) |
+-----------------------------------+
ST_AsGeoJSON
returns the given
geometry as a
GeoJSON element
ST_GeomFromGeoJSON
given a GeoJSON input,
returns a geometry
object:](https://image.slidesharecdn.com/022017emearoadshowmilan-whatsnew-mariadbserver102andmaxscale21-170511204624/85/03-2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale-2_1-22-320.jpg)
![Database
Compatibility
• Multi-Trigger Support per Type
– Beginning with MariaDB Server 10.2, multiple triggers
of the same type (BEFORE, AFTER) can be created per
table
– The CREATE TRIGGER Statement now allows to define
[{ FOLLOWS | PRECEDES } other_trigger_name ]
when creating a trigger
• CHECK constraints allow data validation per column
– Check constraints helps a DBA to enforce data consistency
on the database server level without the need to implement
triggers
• EXECUTE IMMEDIATE for dynamic SQL combines
prepare, execute and deallocate prepare into one
action
• DECIMAL increased from 30 to 38 digits
• Support of expressions for DEFAULT
Increased Database
Compatibility by reducing
limitation based workflows
can now be built based on
triggers](https://image.slidesharecdn.com/022017emearoadshowmilan-whatsnew-mariadbserver102andmaxscale21-170511204624/85/03-2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale-2_1-26-320.jpg)
![Security
• HIPPA/PCI Compliance: Selective Data Masking based on column name
– Database name, Table name classifier may be provided
• commerceDb.customerTbl.creditcardNum
• customerTbl.creditcardNum
• credicardNum
SELECT Name, creditcardNum, balance
FROM customerTbl
WHERE id=1001
Name creditcardNum
balance
---------------------------------------
John Smith xxxxxxxxxx
1201.07
Client
MaxScale
Database Servers
"rules":
[
{
"replace":
{
"column":
"creditcardNum"
},
"with":
{
"value":
"XXXXXXXXX",
“fill":
"0"
}
},
...
]](https://image.slidesharecdn.com/022017emearoadshowmilan-whatsnew-mariadbserver102andmaxscale21-170511204624/85/03-2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale-2_1-47-320.jpg)
03 2017Emea_RoadshowMilan-WhatsNew-Mariadbserver10_2andmaxscale 2_1
- 1. What’s New in MariaDB Server 10.2 and MariaDB MaxScale 2.1
- 2. What’s New in MariaDB Server 10.2
- 5. Window Functions • Window functions were introduced in SQL:2003. The last expansion was in the latest version of the standard, SQL:2011. • A window function looks at “windows” of your data while processing it, which improves the efficiency of query execution. • Identified by the OVER clause • Window functions – can help eliminate expensive subqueries – can help eliminate self-joins – make queries more readable – make queries faster More efficient and readable queries, especially powerful when analyzing data
- 6. Window Functions Data Series Example SELECT time, value FROM data_points ORDER BY time;
- 7. Window Functions Data Series Example SELECT time, value FROM data_points ORDER BY time; SELECT time, value, avg(value) over (ORDER BY time ROWS BETWEEN 6 PRECEDING AND 6 FOLLOWING) FROM data_points ORDER BY time;
- 8. Window Functions Data Series Example SELECT timestamp, transaction_id, customer_id, amount, (SELECT sum(amount) FROM transactions AS t2 WHERE t2.customer_id = t1.customer_id AND t2.timestamp <= t1.timestamp) AS balance FROM transactions AS t1 ORDER BY customer_id, timestamp; SELECT timestamp, transaction_id, customer_id, amount, sum(amount) OVER (PARTITION BY customer_id ORDER BY timestamp ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS balance FROM transactions AS t1 ORDER BY customer_id, timestamp; Query using Window function Query without Window function
- 9. Window Functions Example: Given a set of bank transactions, compute the account balance after each transaction *Test done in a developer environment #Rows Regular SQL (seconds) Regular SQL + Index (seconds) Window Functions (seconds) 10 000 0.29 0.01 0.02 100 000 2.91 0.09 0.16 1 000 000 29.1 2.86 3.04 10 000 000 346.3 90.97 43.17 100 000 000 4357.2 813.2 514.24
- 10. Window Functions • MariaDB supports – ROWS and RANGE-type frames – "Streamable" window functions: ROW_NUMBER, RANK, DENSE_RANK – Window functions that can be streamed once the number of rows in partition is known: PERCENT_RANK, CUME_DIST, NTILE – Aggregate functions that are currently supported as window functions are: COUNT, SUM, AVG, BIT_OR, BIT_AND, BIT_XOR. – Aggregate functions with the DISTINCT specifier (e.g. COUNT( DISTINCT x)) are not supported as window functions. Supported Functions
- 11. Analytics SQL Common Table Expressions (CTE)
- 12. CTE • Hierarchical and recursive queries for SQL were introduced in SQL:1999 and were implemented as common table expressions (CTEs) • A Common Table Expression is basically a temporary and named result set, derived from a simple query • A CTE – is identified by a WITH clause – Similar to derived tables in the FROM clause – More expressive and provide cleaner code – Can produce more efficient query plans – Can be used with SELECT and EXPLAIN Refer to a subquery expression many times in a query. A temporary table that only exists for the duration of a query.
- 13. Common Table Expression Example WITH sales_product_year AS ( SELECT product, year(ship_date) as year, SUM(price) as total_amt FROM item_sales GROUP BY product, year ) SELECT * FROM sales_product_year CUR, sales_product_year PREV, WHERE CUR.product = PREV.product AND CUR.year = PREV.year + 1 AND CUR.total_amt > PREV.total_amt; Use CTE Define CTE
- 14. JSON JSON & GeoJSON Functions
- 15. JSON • JSON (Java Script Object Notation), a text based and platform independent data exchange format • MariaDB Server provides – JSON functions which gives users the highest flexibility to work with JSON based data – stored in string based data types like VARCHAR. • Storing JSON data in MariaDB Server is combining relational data with the world of NoSQL • MariaDB Server currently supports 24 JSON functions to evaluate, query and modify JSON formatted strings JSON- and GeoJSON Functions for MariaDB
- 16. JSON Example Working with JSON Data CREATE TABLE jsontable ( id INTEGER NOT NULL PRIMARY KEY AUTO_INCREMENT, jsonfield VARCHAR(1024), category VARCHAR(20) as (JSON_VALUE(jsonfield,'$.category')), KEY jsonkey (category), CHECK (JSON_VALID(jsonfield))); Field for JSON Data Virtual column for Index on JSON key Constraint to validate JSON format
- 17. JSON Example Insert JSON Data INSERT INTO jsontable (id,jsonfield) VALUES(NULL, '{"category": "Software","product": "MaxScale", "version": "2.0.0"}'); INSERT INTO jsontable (id,jsonfield) VALUES(NULL, '{"category": "Service","service_type": "Training", "class": "DBA"}'); SELECT * FROM jsontableG ******************* 1. row *********************** id: 1 jsonfield: {"category": "Software","product": "MaxScale", "version": "2.0.0"} category: Software Insert like a string JSON_VALUE based Virtual Column entry
- 18. JSON Example Validating JSON Format INSERT INTO jsontable (id,jsonfield) VALUES(NULL, '{"category" - "Software","product": "MaxScale", "version": "2.0.0"}'); ERROR 4025 (23000): CONSTRAINT `CONSTRAINT_1` failed for `test`.`jsontable` Insert non JSON format Validation JSON_VALID fails
- 19. JSON Function Examples SELECT JSON_ARRAY(56, 3.1416, 'My name is "Foo"', NULL); +--------------------------------------------------+ | Json_Array(56, 3.1416, 'My name is "Foo"', NULL) | +--------------------------------------------------+ | [56, 3.1416, "My name is "Foo"", null] | +--------------------------------------------------+ SELECT JSON_OBJECT("id", 1, "name", "Monty"); +---------------------------------------+ | JSON_OBJECT("id", 1, "name", "Monty") | +---------------------------------------+ | {"id": 1, "name": "Monty"} | +---------------------------------------+ JSON array from listed values JSON object from key,value pairs
- 20. JSON Function Examples SELECT json_query('{"key1":123, "key1": [1,2,3]}', '$.key1'); +-------------------------------------------------------+ | json_query('{"key1":123, "key1": [1,2,3]}', '$.key1') | +-------------------------------------------------------+ | [1,2,3] | +-------------------------------------------------------+ select json_query('{"key1":{"a":1, "b":[1,2]}}', '$.key1'); +-----------------------------------------------------+ | json_query('{"key1":{"a":1, "b":[1,2]}}', '$.key1') | +-----------------------------------------------------+ | {"a":1, "b":[1,2]} | +-----------------------------------------------------+ query JSON array query JSON object
- 21. GeoJSON • With MariaDB Server 10.2 GeoJSON functions have been added to the existing functions used to work with spatial data types, like POINT, LINESTRING, POLYGON • ST_AsGeoJSON is used to convert a geometric data type into a GeoJSON format • ST_GeomFromGeoJSON is used to convert a GeoJSON based description into a geometric format • The GeoJSON format follows the open standard for encoding geometric features - http://geojson.org GeoJSON functions for converting a geometry to a GeoJSON element or vise versa
- 22. JSON Function Examples SELECT ST_AsGeoJSON(ST_GeomFromText('POINT(5.3 7.2)')); +-------------------------------------------------+ | ST_AsGeoJSON(ST_GeomFromText('POINT(5.3 7.2)')) | +-------------------------------------------------+ | {"type": "Point", "coordinates": [5.3, 7.2]} | +-------------------------------------------------+ SET @j = '{ "type": "Point", "coordinates": [5.3, 15.0]}'; SELECT ST_AsText(ST_GeomFromGeoJSON(@j)); +-----------------------------------+ | ST_AsText(ST_GeomFromGeoJSON(@j)) | +-----------------------------------+ | POINT(5.3 15) | +-----------------------------------+ ST_AsGeoJSON returns the given geometry as a GeoJSON element ST_GeomFromGeoJSON given a GeoJSON input, returns a geometry object:
- 23. Replication Delayed Replication & more
- 24. New Replication Features • Delayed Replication – allows specifying a slave to lag behind the master – CHANGE MASTER TO master_delay=3600; • Restrict the speed of reading binlog from Master – The option read_binlog_speed_limit can be used to restrict the speed to read the binlog from the master – Reduces the load on the master when slaves need to catch up • Compressed Binary Log – Reduced Binary Log size and network traffic – Binary Log events are compressed on the master – The slave IO thread is uncompressing them before writing them into the Relay Log – Compression is controlled by log_bin_compress and log_bin_compress_min_len New Replication Features help to reduce load on Master, disk space, network bandwidth usage
- 26. Database Compatibility • Multi-Trigger Support per Type – Beginning with MariaDB Server 10.2, multiple triggers of the same type (BEFORE, AFTER) can be created per table – The CREATE TRIGGER Statement now allows to define [{ FOLLOWS | PRECEDES } other_trigger_name ] when creating a trigger • CHECK constraints allow data validation per column – Check constraints helps a DBA to enforce data consistency on the database server level without the need to implement triggers • EXECUTE IMMEDIATE for dynamic SQL combines prepare, execute and deallocate prepare into one action • DECIMAL increased from 30 to 38 digits • Support of expressions for DEFAULT Increased Database Compatibility by reducing limitation based workflows can now be built based on triggers
- 27. CHECK Constraints Examples CREATE TABLE t1 (a INT CHECK (a>2), b INT CHECK (b>2), CONSTRAINT a_greater CHECK (a>b)); CREATE TABLE t2 (name VARCHAR(30) CHECK (CHAR_LENGTH(name)>2), start_date DATE, end_date DATE CHECK (start_date IS NULL OR end_date IS NULL OR start_date<end_date)); CREATE TABLE jsontable ( id INTEGER NOT NULL PRIMARY KEY AUTO_INCREMENT, jsonfield VARCHAR(1024), category VARCHAR(20) as (JSON_VALUE(jsonfield,'$.category')), KEY jsonkey (category), CHECK (JSON_VALID(jsonfield))); Numeric constraints and comparisons Date comparisons and character length Validation by using functions
- 29. Enhancements from MySQL InnoDB 5.7 • Some of the InnoDB 5.7 enhancements are: – Indexes for spatial data types – VARCHAR size can be increased using an in-place ALTER TABLE, if the length stays between 0 and 255 or higher than 255 – improved DDL performance for InnoDB temporary tables – InnoDB internal improvements and better control via parameters – On Fusion-io Non-Volatile Memory (NVM) file systems the doublewrite buffer is automatically disabled for system tablespace files – Optimized crash recovery (tablespace discovery) MySQL Server 5.7 has introduced enhancements to InnoDB, some selected changes have been merged to MariaDB Server
- 30. MyRocks Storage Engine • For workloads requiring higher compression and IO efficiency • Higher performance for web scale type applications • LSM (Log-structured merge) architecture allows very efficient data ingestion • Extract of the available features – Column Families – Transactions and WriteBatchWithIndex – Backup and Checkpoints – Merge Operators – Manual Compactions Run in Parallel with Automatic Compactions – Persistent Cache – Bulk loading – Delete files in range – Pin iterator key/value MyRocks in MariaDB, compression and IO efficiency based on Facebook’s MyRocks.
- 31. Performance
- 32. Performance Optimizations • Enhanced Performance for creating Connections – The way to create new connections has been optimized – This is especially good for applications, which are using non-persistent connections • Indexes for Virtual Columns – Before MariaDB Server 10.2 indexes could not be defined for virtual columns – With supporting indexes, virtual columns also can be used efficiently for searching • New Option to define a directory for InnoDB temporary files – By using a separate directory for InnoDB temporary files separate disks and types of disks can be used, which is reducing IO waits Several changes have been added to MariaDB Server to improve Performance
- 33. Security
- 34. New Security related User options • Per User Server Load Limitations – Limit to the number of queries, updates or connections the user can place or make per hour. – Limit to the number of simultaneous connections that the user can hold • Enforced TLS connections – SSL/TLS encryption options have been introduced for users, permitting only encrypted connections for a user – CREATE and ALTER USER now include the optional parameters SSL, X509, ISSUER, SUBJECT, CIPHER Limit the load a user can add to the server; enforce secure connections
- 35. Security Syntax Enhancements Examples CREATE USER foo WITH MAX_QUERIES_PER_HOUR 10 MAX_UPDATES_PER_HOUR 20 MAX_CONNECTIONS_PER_HOUR 30 MAX_USER_CONNECTIONS 40; CREATE USER 'foo4'@'test' REQUIRE ISSUER 'foo_issuer' SUBJECT 'foo_subject' CIPHER 'text; Per User Server Load Limitation Enforced TLS Connections
- 36. Administration
- 37. New options for DBAs • New functions for User Management – ALTER USER – SHOW CREATE USER • Enhanced Informations from EXPLAIN – EXPLAIN FORMAT=JSON for detailed information on sort_key an outer_ref_condition • User defined variables added to Information Schema – Information schema plugin to report all user defined variables via the Information Schema USER_VARIABLES Table • Binary Log based Flashback – The MariaDB Flashback feature allows DBAs to roll back instances, databases or tables to a given timestamp
- 38. Summary - What’s New Analytics SQL ● Window Functions ● Common Table Expressions (CTE) JSON ● JSON Functions ● GeoJSON Functions Replication ● Delayed Replication ● Restrict the speed of reading binlog from Master ● Compressed Binary Log Database Compatibility ● Multi-Trigger Support ● CHECK Constraint Expression Support ● EXECUTE IMMEDIATE statement ● Support for DEFAULT with expressions ● DECIMAL increased from 30 to 38 digits Storage Engine Enhancements ● New Storage Engine MyRocks based on RocksDB from Facebook ● Enhancements from MySQL InnoDB 5.7 ● Enable InnoDB NUMA interleave for InnoDB
- 39. Summary - What’s New Security ● Per User Server Load Limitations ● Enforced TLS Connections Administration ● New functions for User Management ● Enhanced Informations from EXPLAIN ● User defined variables added to Information Schema ● Binary Log based Flashback Performance ● Enhanced Performance for creating Connections ● Indexes for Virtual Columns ● New Option to define a directory for InnoDB temporary files Server-Internal Optimisations ● Internal Use of MariaDB Connector/C ● Optimizer Enhancements ● Non-Locking ANALYZE TABLE Other Enhancements ● Lifted limitations for Virtual Computed Columns ● Subquery-Support for Views ● Multiple Use of Temporary Tables in Query
- 40. What’s New in MariaDB MaxScale 2.1
- 41. 41 MariaDB MaxScale Database Proxy platform for ● Scalability ● Security ● High Availability ● Data Streaming ● Latest GA Version 2.0 ● Soon to be GA version 2.1 ● Part of MariaDB Enterprise Offering MaxScale MaxScale
- 42. MariaDB MaxScale Concept Generic Core ▪ Multi-threaded ▪ e-poll based ▪ Stateless ▪ Shares the thread pool Flexible, easy to write plug-ins for ▪ Protocol support ▪ Authentication ▪ Database monitoring ▪ Load balancing and routing ▪ Query Transformation and logging ProtocolCore Rou$ng Database Servers MaxScale MaxScale Master Slaves Binlog Cache ● Insulates client applications from the complexities of backend database cluster ● Simplify replication from database to other databases Client
- 43. What is new in MariaDB MaxScale 2.1 ? • Performance – Up to 2.8x improvement over MaxScale 2.0 • Security – Encrypted binlog server files – SSL between binlog server and Master/Slave – LDAP/GSSAPI Authentication support – Selective Data Masking – Maximum rows returned limit – Prepared Statement filtering by database firewall • Scalability – Aurora Cluster support – Consistent Critical Read with Master Pinning – Query Cache Filter – Streaming Insert Plugin • Ease of use – Dynamic Configuration of server, monitor, listener and firewall rules
- 44. Up to 2.8 x Performance Gain MaxScale 2.1 Performance Gain Read Only Read Write QPSQPS Number of Connections
- 45. Security in MaxScale 2.1 • Existing in MaxScale 2.0 – End to End SSL for transport layer security between applications, proxy & databases – Black and white list with Database Firewall Filter for SQL Injection protection – Connection Rate Limitation for DDoS protection • New in MaxScale 2.1 – Encrypted binlog server files – SSL between binlog server and Master/Slave – LDAP/GSSAPI Authentication support – Selective Data Masking – Maximum rows returned limit – Prepared Statement and Functions filtering by database firewall
- 46. • Secured Binlog Server – Encrypt binlog server files on MaxScale – SSL between binlog server and Master/Slave • Secured user access – LDAP/GSSAPI for secured single sign-on across OS platforms(windows, linux), applications and databases Slaves Security Master Slaves SSL SSL SSL SSL Binlog Cache Binlog Cache MaxScale MaxScale
- 47. Security • HIPPA/PCI Compliance: Selective Data Masking based on column name – Database name, Table name classifier may be provided • commerceDb.customerTbl.creditcardNum • customerTbl.creditcardNum • credicardNum SELECT Name, creditcardNum, balance FROM customerTbl WHERE id=1001 Name creditcardNum balance --------------------------------------- John Smith xxxxxxxxxx 1201.07 Client MaxScale Database Servers "rules": [ { "replace": { "column": "creditcardNum" }, "with": { "value": "XXXXXXXXX", “fill": "0" } }, ... ]
- 48. Security • DDoS Protection • Maximum rows filter – Return zero rows to client if number of rows in result set exceeds configured max limit – Return zero rows to client if the size of result set exceeds configured max size in KB MaxRowsLimit Filter Max Rows Limit = 500 NumRows Returned > MaxRows Limit NumRows returned = 1000 5 Query result: Error or Empty result set Query Query 4 1 32 MaxScale Clients Database Servers Configuration: max_resultset_return=empty|error|ok max_resultset_size=128Ki max_resultset_rows=1000
- 49. Security • SQL Injection Protection – Prepared Statement filtering by database firewall • Apply database firewall rules to prepared statements – Function name filtering by database firewall • Black/White list query based on specific function being called in the SQL -‐ Block queries wildcard * -‐ Prevent rapid execution of specific queries -‐ Block queries without WHERE clause Example: with rules.conf rule limit_rate deny limit_queries 10 5 60 rule peak_hours deny wildcard at_times 17:00:00-‐17:30:00 rule safe_del deny no_where_clause on_queries delete rule query_regex deny regex '.*select.*from.*user_data.*'
- 50. Scalability with MaxScale 2.1 • Existing in MaxScale 2.0 – Transaction Scaling to support user growth and simplify applications • MariaDB Master/Slave and MariaDB Galera Cluster – Load balancing – Database aware dynamic query routing – Traffic profile based routing – Replication Scaling to support web-scale applications’ user base • Binlog Server for horizontal scaling of slaves in Master/Slave architecture – Multi-tenant database scaling to transparently grow tenants and data volume • Schema sharding – Connection Rate Limitation • New in MaxScale 2.1 – Aurora Cluster Monitor – Multi-master and Failover mode for MySQL Monitor – Consistent Critical Read Filter: Master Pinning
- 51. Aurora Cluster Monitoring and Routing • Aurora Cluster Monitor – Detect read replicas and write node in Aurora Cluster – Supports launchable scripts on monitored events like other monitors – Read-Write Splitting, Read Connect Routing, Schema Routing now can be used for Aurora Cluster Read Write Primary Read Replicas MaxScale
- 52. Consistent Critical Read • Master Pinning: Consistent Critical Read Filter – Detects a statement that would modify the database and route all subsequent statement to the master server where data is guaranteed to be in a up-to-date state match=.*INSERT.* // which statements trigger the statement re-routing time=5 // Time window for routing queries to master Result: INSERT INTO db1.tbl1 (id, name) VALUES(100, ‘Dan’); // sent to master SELECT @@server_id; // forced route to master SELECT name FROM db1.tbl1 WHERE name = ‘Dan’; // forced route to master
- 53. Query Cache • New in MaxScale 2.1 – Query Cache Filter • Cache query results in MaxScale for configurable timeout • For the configurable timeout, return results from cache before being refreshed from to server • Configured like any other filter. caching rules can be specified in a separate json-file: rules=/path/to/rules-‐ file.json In memory LRU cache. MaxScale Clients Database Servers
- 54. Batch Insert • New in MaxScale 2.1 – Streaming Insert Plugin • Convert all INSERT statements done inside an explicit transaction into LOAD DATA LOCAL INFILE • Useful for client applications doing many inserts within a transaction • Improves performance of data load INSERT INTO test.t1 VALUES (“John Doe”, 1234, “1234-‐5678-‐ABCD”), (“Jane Doe”, 4321, “8765-‐4321-‐DCBA”); “John Doe”, 1234, “1234-‐5678-‐ABCD” “Jane Doe”, 4321, “8765-‐4321-‐DCBA” LOAD DATA LOCAL INFILE ‘maxscale.data’ INTO TABLE test.t1 FIELDS TERMINATED BY ‘,’ LINES TERMINATED BY ‘n’;
- 55. Ease of Use • New in MaxScale 2.1 – Dynamically configure server, listener, monitor • Add/Remove new server to configuration • Add/Remove new listener to configuration • Add/Remove monitor to configuration • No MaxScale restart require – Dynamically configure database firewall rules • Modify firewall rules while MaxScale is running – Support for text wildcards in hostnames – New global setting log_throttling to throttle flooding of log file
- 56. Future • MariaDB 10.2 Support • Cross Data Center HA enablement • PAMD Authentication • More performance enhancement • Additional protocols • Tighter integration with MariaDB ColumnStore MaxScale
- 57. Thank you Maria Luisa Raviol Senior Sales Engineer mluisa.raviol@mariadb.com Massimiliano Pinto Senior Software Solutions Engineer massimiliano.pinto@mariadb.com