text:
Q: Datastax c# Cassandra throwing exception after update to 3.X I've just upgraded the driver from 2.7.3 to 3.0.3 and seems like something weird was done with the Mapper.Single() . It was just working on the old version but now throws an exception;
Exception thrown: 'System.ArgumentException' in Cassandra.dll ("Argument types do not match")

Schema:
CREATE TABLE IF NOT EXISTS client (
    id uuid PRIMARY KEY,
    timezone frozen<timezone>,
    language frozen<language>,
    bank set<frozen<bank>>,
    name text,
    country frozen<country>
);

CREATE TYPE IF NOT EXISTS timezone (
    id uuid,
    name text,
    time int
);

CREATE TYPE IF NOT EXISTS language (
    id uuid,
    name text,
    iso text
);

CREATE TYPE IF NOT EXISTS bank (
    id uuid,
    name text,
    number int
);
CREATE TYPE IF NOT EXISTS country (
    id uuid,
    name text,
    iso2 text,
    iso3 text
);

Mappings
For<Client>()
            .TableName("client")
                  .PartitionKey(u => u.Id)
                  .Column(u => u.Id, cm => cm.WithName("id"))
                  .Column(u => u.Name, cm => cm.WithName("name").WithSecondaryIndex())
                  .Column(u => u.Timezone, cm => cm.WithName("timezone"))
                  .Column(u => u.Language, cm => cm.WithName("language"))
                  .Column(u => u.Country, cm => cm.WithName("country"))
                  .Column(u => u.Banks, cm => cm.WithName("bank"));

UdtMap.For<Timezone>()
                 .Map(u => u.Id, "id")
                 .Map(u => u.Name, "name")
                 .Map(u => u.Time, "time")
UdtMap.For<Bank>()
                .Map(u => u.Id, "id")
                .Map(u => u.Number, "number")
                .Map(u => u.Name, "name")
UdtMap.For<Language>()
                  .Map(u => u.Id, "id")
                  .Map(u => u.Name, "name")
                  .Map(u => u.Iso, "iso")
UdtMap.For<Country>()
               .Map(u => u.Id, "id")
               .Map(u => u.Name, "name")
               .Map(u => u.Iso2, "iso2")
               .Map(u => u.Iso3, "iso3")

C# Code
public static class CassandraConnection
    {
        private static Cluster Cluster;
        public static String Keyspace { get; set; }
        public static String[] Addresses { get; set; }
        public static String Username { get; set; }
        public static String Password { get; set; }
        public static ISession Session { get; set; }
        public static MappingConfiguration MappingConfiguration { get; set; }
        public static IMapper Mapper { get; set; }
        public static void Conectar()
        {
            Addresses = CloudConfigurationManager.GetSetting("Cassandra.Addresses").Split(';');
            Keyspace = CloudConfigurationManager.GetSetting("Cassandra.Keyspace");

            Username = CloudConfigurationManager.GetSetting("Cassandra.Username");
            Password = CloudConfigurationManager.GetSetting("Cassandra.Password");

            if (String.IsNullOrEmpty(Username))
            {
                CassandraConnection.Cluster = Cluster.Builder().AddContactPoints(Addresses).Build();
            }
            else
            {
                CassandraConnection.Cluster = Cluster.Builder().AddContactPoints(Addresses).WithCredentials(Username, Password).Build();
            }
            CassandraConnection.Session = CassandraConnection.Cluster.Connect(Keyspace);
            MappingConfiguration.Global.Define<MapCassandra>();
            Session.UserDefinedTypes.Define(UdtCassandra.Udts());
            CassandraConnection.Mapper = new Mapper(CassandraConnection.Session);
        }

    }

 public class CassandraRepository<T> : IRepository<T> where T : BaseDomain
    {
        public T GetById(T entity)
        {
            if(CassandraConnection.Session == null)
            {
                CassandraConnection.Conectar();
            }
            if (entity != null)
            {
                return CassandraConnection.Mapper.Fetch<T>("WHERE id = ?", entity.Id).FirstOrDefault(); //That should be just SingleOrDefault() but im testing stuff;
            }
            return default(T);
        }
}

StackTrace
 em System.Linq.Expressions.Expression.Condition(Expression test, Expression ifTrue, Expression ifFalse)
   em Cassandra.Mapping.MapperFactory.GetExpressionToGetColumnValueFromRow(ParameterExpression row, CqlColumn dbColumn, Type pocoDestType)
   em Cassandra.Mapping.MapperFactory.CreateMapperForPoco[T](RowSet rows, PocoData pocoData)
   em Cassandra.Mapping.MapperFactory.CreateMapper[T](RowSet rows)
   em Cassandra.Mapping.MapperFactory.<>c__DisplayClass1`1.<GetMapper>b__0(Tuple`2 _)
   em System.Collections.Concurrent.ConcurrentDictionary`2.GetOrAdd(TKey key, Func`2 valueFactory)
   em Cassandra.Mapping.MapperFactory.GetMapper[T](String cql, RowSet rows)
   em Cassandra.Mapping.Mapper.<>c__DisplayClass7`1.<FetchAsync>b__6(Statement s, RowSet rs)
   em Cassandra.Mapping.Mapper.<>c__DisplayClass2`1.<>c__DisplayClass4.<ExecuteAsyncAndAdapt>b__1(Task`1 t2)
   em Cassandra.Tasks.TaskHelper.DoNext[TIn,TOut](Task`1 task, Func`2 next)
   em Cassandra.Tasks.TaskHelper.WaitToComplete(Task task, Int32 timeout)
   em Cassandra.Tasks.TaskHelper.WaitToComplete[T](Task`1 task, Int32 timeout)
   em Cassandra.Mapping.Mapper.Fetch[T](Cql cql)
   em Cassandra.Mapping.Mapper.Fetch[T](String cql, Object[] args)
   em CassandraWebTest.Repository.Cassandra.CassandraRepository`1.GetById(T entity) na C:\Users\devb0194\Source\Workspaces\CassandraWebTestV3\CassandraWebTest.Repository\Cassandra\CassandraRepository.cs:linha 124
   em CassandraWebTest.Business.Security.Client.GetById(Client Client) na C:\Users\devb0194\Source\Workspaces\CassandraWebTestV3\CassandraWebTest.Business\Security\Client.cs:linha 63
   em CassandraWebTest.Business.Security.UsuarioAutenticacao.Authenticate(UsuarioAutenticacao usuarioAutenticacao) na C:\Users\devb0194\Source\Workspaces\CassandraWebTestV3\CassandraWebTest.Business\Security\UsuarioAutenticacao.cs:linha 95
   em CassandraWebTest.Web.Controllers.LoginController.Authenticate(String usuario, String senha, Boolean persistente) na C:\Users\devb0194\Source\Workspaces\CassandraWebTestV3\Web\CassandraWebTest.Web\Controllers\LoginController.cs:linha 38

This code works fast and perfectly on 2.7.X but doesnt work on 3.X.X drivers.

A: Error was due one of the POCO's got a reference to a frozen type using IList instead IEnumerable.
That used to work on 2.7.X but doesnt work on 3.X.X.
Thanks a lot Jorge!

redpajama_set_name: RedPajamaStackExchange


text:
package org.fest.assertions;

import org.junit.After;
import org.junit.Before;
import org.junit.Test;

import static org.fest.assertions.Mocks.createComparisonFailureFrom;
import static org.junit.Assert.assertNull;
import static org.mockito.Mockito.mock;
import static org.mockito.Mockito.when;

/**
 * Tests for {@link ComparisonFailureFactory#comparisonFailure(String, Object, Object)}.
 *
 * @author Alex Ruiz
 */
public class ComparisonFailureFactory_comparisonFailure_withMocks_Test {
  private ConstructorInvoker invoker;

  @Before
  public void setUp() {
    invoker = mock(ConstructorInvoker.class);
    ComparisonFailureFactory.constructorInvoker(invoker);
  }

  @After
  public void tearDown() {
    ComparisonFailureFactory.constructorInvoker(new ConstructorInvoker());
  }

  @Test
  public void should_return_null_if_created_Object_is_not_AssertionError() {
    when(createComparisonFailure()).thenReturn(new Object());
    AssertionError created = ComparisonFailureFactory.comparisonFailure("message", "expected", "actual");
    assertNull(created);
  }

  @Test
  public void should_return_null_if_call_to_constructor_throws_exception() {
    when(createComparisonFailure()).thenThrow(new RuntimeException());
    AssertionError created = ComparisonFailureFactory.comparisonFailure("message", "expected", "actual");
    assertNull(created);
  }

  private Object createComparisonFailure() {
    return createComparisonFailureFrom(invoker);
  }
}

redpajama_set_name: RedPajamaGithub


Document for OPTIONS syntax in /etc/make.conf, where to find?
Previous message (by thread): Document for OPTIONS syntax in /etc/make.conf, where to find?
> > possibly several times until there is nothing more left to configure, as I did when using portupgrade and later portmaster.
I already have read the man page because I git-cloned synth tree from github repository.
I want to keep the Ada code for viewing, among other things.
My first attempt to build synth was on FreeBSD-current amd64 and failed when the system rebooted itself when I was sleeping.  Apparently no filesystem damage.
System came up in System Rescue CD 5.0.0 USB-stick installation.
I attribute this to FreeBSD-current instability rather than synth or ports, meaning I must first rebuild FreeBSD 11.0-STABLE amd64 installation, and then from there, FreeBSD-current amd64.


text:
These are the world's 10 most popular spots to pop the question
So, it's safe to say that asking someone to marry you/ being asked to marry someone is probably one of the most important moments of your entire life.
Apart from worrying about whether or not they'll actually say yes, there's a lot of planning and logistics that go into making the perfect proposal – after all, you're going to remember it forever, so it's worth pulling out all the stops.
Stepping away from the traditional 'make a show of you in front of a restaurant full of diners approach', more and more people are opting to pop the question at some of the world's most famous locations.
In an effort to find out where people are most likely to get down on one knee, hitched.co.uk analysed 10,000 hashtags, such as #bridetobe and #engaged, and used the information to compile a list of the 10 most popular proposal spots across the world.
1.Disneyland, Paris
Often dubbed the happiest place on planet earth, it's hardly surprising that one in 500 proposals take place inside the gates of the theme park.
2. Walt Disney's Magic Kingdom, Florida
It looks like nothing cam stop the magic of Disney with one in 555 questions popped at the Magic Kingdom in Orlando.
3. Centennial Lakes Park, Minnesota
24 acres of stunning greenery located in the heart of the USA. A firm favourite for happy couples with one in 625 proposals taking place here.
4. Eiffel Tower, Paris
The city of love strikes again, with one in 679 couples getting engaged at one of Europe's most romantic locations.
5.The Hollywood Sign, LA
Adding a bit of showbiz to the nuptials, one in every 1,000 proposals takes place in the Hollywood hills.
6. Central Park and Brooklyn Bridge, New York
A double whammy for NYC with two of it's most iconic landmarks sharing the number six spot. One in 1,111 proposals respectively.
7.Niagara Falls, Ontario
Without a doubt, one of the most stunning sights on planet earth, Niagra Falls acts as the backdrop for one in 1,250 proposals.
8. Walt Disney's Epcot Park, Florida
A third appearance for Disney, with Epcot playing host to one in 1,428 proposals.
9. Big Bear Lake, California
With chilled vibes and stunning views, it;s no wonder this picturesque location sees one on 1,666 take place here.
10. Bondi Beach, Sydney
One in 2,000 proposals happen on the sandy shores of one of the world's most iconic beaches.
pop the big question

redpajama_set_name: RedPajamaCommonCrawl


In multi-master use of BDR writes to the same or related table(s) from multiple different nodes can result in data conflicts.
Some clustering systems use distributed lock mechanisms to prevent concurrent access to data. These can perform reasonably when servers are very close but cannot support geographically distributed applications as very low latency is critical for acceptable performance.
Distributed locking is essentially a pessimistic approach, whereas BDR advocates an optimistic approach: avoid conflicts where possible but allow some types of conflict to occur and and resolve them when they arise.


Oracle Exadata Storage Server is a highly optimized storage server that runs Oracle Exadata System Software to store and access Oracle Database data.
With traditional storage, data is transferred to the database server for processing. In contrast, Oracle Exadata System Software provides database-aware storage services, such as the ability to offload SQL and other database processing from the database server, while remaining transparent to the SQL processing and database applications. Oracle Exadata Storage Servers process data at the storage level, and pass only what is needed to the database server.
Oracle Exadata System Software is installed on both the storage servers and the database servers. Oracle Exadata System Software offloads some SQL processing from the database server to the Oracle Exadata Storage Servers. Oracle Exadata System Software enables function shipping between the database instance and the underlying storage, in addition to traditional data shipping. Function shipping greatly reduces the amount of data processing that must be done by the database server. Eliminating data transfers and database server workload can greatly benefit query processing operations that often become bandwidth constrained. Eliminating data transfers can also provide a significant benefit to online transaction processing (OLTP) systems that include large batch and report processing operations.
The hardware components of Oracle Exadata Storage Server are carefully chosen to match the needs of high performance processing. The cell software is optimized to maximize the advantage of the hardware components. Each cell delivers outstanding processing bandwidth for data stored on disk, often several times better than traditional solutions.
Oracle Exadata Storage Servers use state-of-the-art InfiniBand interconnections between servers and storage. Each InfiniBand link provides 40 gigabits per second of bandwidth, many times higher than traditional storage or server networks. Additionally, Oracle interconnection protocol uses direct data placement, also referred to as direct memory access (DMA), to ensure low CPU overhead by directly moving data from the wire to database buffers with no extra copies. The InfiniBand network has the flexibility of a LAN network with the efficiency of a storage area network (SAN). With an InfiniBand network, Oracle Exadata Database Machine eliminates network bottlenecks that could reduce performance. This InfiniBand network also provides a high performance cluster interconnection for Oracle Real Application Clusters (Oracle RAC)servers.
The Oracle Exadata Storage Server architecture scales to any level of performance. To achieve higher performance or greater storage capacity, you add more storage cells to the configuration. As more cells are added, capacity and performance increase linearly. Data is mirrored across cells to ensure that the failure of a cell does not cause loss of data or availability. The scale-out architecture achieves near infinite scalability, while lowering costs by allowing storage to be purchased incrementally on demand.
Oracle Exadata System Software enables cost-effective modular storage hardware to be used in a scale-out architecture while providing a high level of availability and reliability. All single points of failure are eliminated in the Oracle Exadata Storage Server architecture by data mirroring, fault isolation technology, and protection against disk and other storage hardware failure.
In the Oracle Exadata Storage Server architecture, one or more storage cells can support one or more databases. The placement of data is transparent to database users and applications. Storage cells use Oracle Automatic Storage Management (Oracle ASM) to distribute data evenly across the cells. Because Oracle Exadata Storage Servers support dynamic disk insertion and removal, the online dynamic data redistribution feature of Oracle ASM ensures that data is appropriately balanced across the newly added, or remaining, disks without interrupting database processing. Oracle Exadata Storage Servers also provides data protection from disk and cell failures.
If you are using Oracle Exadata System Software 12c Release 1 (12.1) and later releases, then you must also use Oracle Database and Oracle Automatic Storage Management (Oracle ASM) 12c Release 1 (12.1) or a later release.
All Oracle Database features are fully supported with Oracle Exadata System Software. Oracle Exadata System Software works equally well with single-instance or Oracle Real Application Clusters (Oracle RAC) deployments of Oracle Database. Oracle Data Guard, Oracle Recovery Manager (RMAN), Oracle GoldenGate, and other database features are managed the same with Exadata storage cells as with traditional storage. This enables database administrators to use the same tools with which they are familiar.
WriteBack flash cache provides the ability to cache write I/Os directly to PCI flash in addition to read I/Os.
WriteBack flash cache significantly improves the write intensive operations because writing to flash cache is faster than writing to Hard disks. If your application writes intensively and if you find significant waits for "free buffer waits" or high I/O times, you should consider using WriteBack flash cache.
Oracle has implemented smart flash cache directly in Oracle Exadata Storage Server. Oracle Exadata Smart Flash Cache holds frequently-accessed data in very fast flash storage while most data is kept in very cost-effective disk storage. This happens automatically without the user having to take any action. Oracle Exadata Smart Flash Cache is smart because it knows when to avoid trying to cache data that will never be reused or will not fit in the cache. Oracle Database and Oracle Exadata System Software allow the user to provide directives at the database table, index and segment level to ensure that specific data is retained in flash. Tables can be moved in and out of flash with a simple command, without the need to move the table to different tablespaces, files or LUNs as is done with traditional storage using flash disks.
Oracle Exadata Smart Flash technology is also used to reduce the latency of log write I/O operations by eliminating performance bottlenecks that might occur due to database logging. The time to commit user transactions is very sensitive to the latency of log write operations. In addition, many performance-critical database algorithms, such as space management and index splits, are very sensitive to log write latency.
Although the disk controller has a large battery-backed DRAM cache that can accept writes very quickly, some write operations to disk can still be slow during periods of high I/O. Even with relatively few redo log write operations that are slow, these write operations can cause performance issues. It is these situations that Oracle Exadata Smart Flash Log is designed to alleviate.
The goal of the Oracle Exadata Smart Flash Log is to perform redo write operations simultaneously to both flash memory and disk, and complete the write operation when the first of the two completes. This gives Oracle Exadata the best of both worlds by avoiding problems due to latency spikes on either type of media. Smart Flash Logging is most beneficial during busy periods when the disk controller cache occasionally becomes filled with blocks that have not been written to disk and therefore degrades to real disk performance versus disk cache performance. It is important to note that Smart Flash Logging improves latency of log write operations, but it does not improve total disk throughput. If an application is bottlenecked on disk throughput, then Smart Flash Logging can provide little benefit because log response time is not the limiting factor to performance.
It is also crucial to note that the purpose of Smart Flash Logging is not to use flash to consistently beat disk controller performance. It is used as an auxiliary destination that provides low latency when disks occasionally become slow, thus avoiding a negative impact on database performance.
Oracle Exadata Smart Flash Log improves user transaction response time, and increases overall database throughput for I/O intensive workloads by accelerating performance critical database algorithms.
You can use Oracle Exadata Storage Server to consolidate your storage requirements into a central pool that can be used by multiple databases. Oracle Exadata System Software with Oracle Automatic Storage Management (Oracle ASM) evenly distributes the data and I/O load for every database across available disks in the storage pool. Every database can use all of the available disks to achieve superior I/O rates. Oracle Exadata Storage Servers can provide higher efficiency and performance at a lower cost while also lowering your storage administration overhead.
I/O Resource Management (IORM) and the Oracle Database Resource Manager enable multiple databases and pluggable databases to share the same storage while ensuring that I/O resources are allocated across the various databases.
Oracle Exadata System Software works with IORM and Oracle Database Resource Manager to ensure that customer-defined policies are met, even when multiple databases share the grid. As a result, one database cannot monopolize the I/O bandwidth and degrade the performance of the other databases.
IORM enables storage cells to service I/O resources among multiple applications and users across all databases in accordance with sharing and prioritization levels established by the administrator. This improves the coexistence of online transaction processing (OLTP) and reporting workloads, because latency-sensitive OLTP applications can be given a larger share of disk and flash I/O bandwidth than throughput-sensitive batch applications. Oracle Database Resource Manager enables the administrator to control processor utilization on the database host on a per-application basis. Combining IORM and Oracle Database Resource Manager enables the administrator to establish more accurate policies.
IORM also manages the space utilization for Exadata Smart Flash Cache. Critical OLTP workloads can be guaranteed space in Exadata Smart Flash Cache to provide consistent performance.
IORM for a database or pluggable database (PDB) is implemented and managed from the Oracle Database Resource Manager. Oracle Database Resource Manager in the database instance communicates with the IORM software in the storage cell to manage user-defined service-level targets. Database resource plans are administered from the database, while interdatabase plans are administered on the storage cell.
One of the most powerful features of Oracle Exadata System Software is that it offloads the data search and retrieval processing to the storage servers.
Oracle Exadata System Software does this by performing predicate filtering, which entails evaluating database predicates to optimize the performance of certain classes of bulk data processing.
In the preceding example, only rows satisfying the predicate, specified columns, and predicated columns are returned to the database server, eliminating unproductive data transfer to the database server.
Oracle Exadata System Software uses storage-side predicate evaluation that transfers simplified, predicate evaluation operations for table and index scans to the storage cell. This brings the table scan closer to the disk to enable a higher bandwidth, and prevents sending unmatched rows to hosts.
Description of "Figure 1-1 Offloading Data Search and Retrieval"
To optimize the performance of incremental backups, the database can offload block filtering to Oracle Exadata Storage Server.
This optimization is only possible when taking backups using Oracle Recovery Manager (RMAN). The offload processing is done transparently without user intervention. During offload processing, Oracle Exadata System Software filters out the blocks that are not required for the incremental backup in progress. Therefore, only the blocks that are required for the backup are sent to the database, making backups significantly faster.
Data corruptions, while rare, can have a catastrophic effect on a database, and therefore on a business.
Oracle Exadata System Software takes data protection to the next level by protecting business data, not just the physical bits.
The key approach to detecting and preventing corrupted data is block checking in which the storage subsystem validates the Oracle block contents. Oracle Database validates and adds protection information to the database blocks, while Oracle Exadata System Software detects corruptions introduced into the I/O path between the database and storage. It stops corrupted data from being written to disk, and validates data when reading the disk. This eliminates a large class of failures that the database industry had previously been unable to prevent.
Unlike other implementations of corruption checking, checks with Oracle Exadata System Software operate completely transparently. No parameters need to be set at the database or storage tier. These checks transparently handle all cases, including Oracle Automatic Storage Management (Oracle ASM) disk rebalance operations and disk failures.
File creation operations are offloaded to Oracle Exadata Storage Servers. Operations such as CREATE TABLESPACE, which can create one or more files, have a significant increase in speed due to file creation offload.
Oracle Exadata Storage Servers maintain a storage index which contains a summary of the data distribution on the disk.
The storage index is maintained automatically, and is transparent to Oracle Database. It is a collection of in-memory region indexes, and each region index stores summaries for up to eight columns. There is one region index for each 1 MB of disk space. Storage indexes work with any non-linguistic data type, and work with linguistic data types similar to non-linguistic indexes.
Each region index maintains the minimum and maximum values of the columns of the table. The minimum and maximum values are used to eliminate unnecessary I/O, also known as I/O filtering. The cell physical IO bytes saved by storage index statistic, available in the V$SYS_STAT view, shows the number of bytes of I/O saved using storage index. The content stored in one region index is independent of the other region indexes. This makes them highly scalable, and avoids latch contention.
Storage indexes are built automatically after Oracle Exadata System Software receives a query with a comparison predicate that is greater than the maximum or less than the minimum value for the column in a region, and would have benefited if a storage index had been present. Oracle Exadata System Software automatically learns which storage indexes would have benefited a query, and then creates the storage index automatically so that subsequent similar queries benefit.
The effectiveness of storage indexes can be improved by ordering the rows based on columns that frequently appear in WHERE query clauses.
The storage index is maintained during write operations to uncompressed blocks and OLTP compressed blocks. Write operations to Exadata Hybrid Columnar CompressionExadata Hybrid Columnar Compression compressed blocks or encrypted tablespaces invalidate a region index, but not the storage index. The storage index for Exadata Hybrid Columnar Compression is rebuilt on subsequent scans.
The following figure shows a table and region indexes. The values in the table range from one to eight. One region index stores the minimum 1, and the maximum of 5. The other region index stores the minimum of 3, and the maximum of 8.
For a query such as SELECT * FROM TABLE WHERE B<2, only the first set of rows match. Disk I/O is eliminated because the minimum and maximum of the second set of rows do not match the WHERE clause of the query.
In the following figure, there is a table named Orders with the columns Order_Number, Order_Date, Ship_Date, and Order_Item. The table is range partitioned by Order_Date column.
Because the table is partitioned on the Order_Date column, the preceding query avoids scanning unnecessary partitions of the table. Queries on Ship_Date do not benefit from Order_Date partitioning, but Ship_Date and Order_Number are highly correlated with Order_Date. Storage indexes take advantage of ordering created by partitioning or sorted loading, and can use it with the other columns in the table. This provides partition pruning-like performance for queries on the Ship_Date and Order_Number columns.
Using storage index allows table joins to skip unnecessary I/O operations. For example, the following query would perform an I/O operation and apply a Bloom filter to only the first block of the fact table.
SELECT count(*) FROM fact, dim WHERE fact.m=dim.m AND dim.product="Hard drive"
The I/O for the second block of the fact table is completely eliminated by storage index as its minimum/maximum range (5,8) is not present in the Bloom filter.
Oracle Exadata Storage Server is a network-accessible storage device with Oracle Exadata System Software installed on it. The software communicates with the database using a specialized iDB protocol, and provides both simple I/O functionality, such as block-oriented reads and writes, and advanced I/O functionality, including predicate offload and I/O Resource Management (IORM). Each storage cell has physical disks. The physical disk is an actual device within the storage cell that constitutes a single disk drive spindle.
Within the storage cells, a logical unit number (LUN) defines a logical storage resource from which a single cell disk can be created. The LUN refers to the access point for storage resources presented by the underlying hardware to the upper software layers. The precise attributes of a LUN are configuration-specific. For example, a LUN could be striped, mirrored, or both striped and mirrored.
A cell disk is an Oracle Exadata System Software abstraction built on the top of a LUN. After a cell disk is created from the LUN, it is managed by Oracle Exadata System Software and can be further subdivided into grid disks, which are directly exposed to the database and Oracle Automatic Storage Management (Oracle ASM) instances. Each grid disk is a potentially noncontiguous partition of the cell disk that is directly exposed to Oracle ASM to be used for the Oracle ASM disk group creations and expansions.
This level of virtualization enables multiple Oracle ASM clusters and multiple databases to share the same physical disk. This sharing provides optimal use of disk capacity and bandwidth. Various metrics and statistics collected on the cell disk level enable you to evaluate the performance and capacity of Oracle Exadata Storage Servers. IORM schedules the cell disk access in accordance with user-defined policies.
Figure 1-2 illustrates how the components of a cell are related to grid disks.
A LUN is created from a physical disk.
A cell disk is created on a LUN. A segment of cell disk storage is used by the Oracle Exadata System Software system, referred to as the cell system area.
Multiple grid disks can be created on a cell disk.
Description of "Figure 1-2 Oracle Exadata Storage Server Components"
Figure 1-3 illustrates software components in the Oracle Exadata Storage Server environment.
Description of "Figure 1-3 Software Components in the Oracle Exadata Storage Server Environment"
Single-instance or Oracle RAC databases access storage cells using the iDB protocol over an InfiniBand network.
The database server software includes Oracle Exadata System Software functionality.
Storage cells contain cell-based software.
Storage cells are configured on the network, and are managed by the Oracle Exadata System Software CellCLI utility.
Striping database files evenly across all available storage cells and disks for optimal performance.
Using mirroring and failure groups to avoid any single point of failure.
Enabling dynamic add and drop capability for nonintrusive cell and disk allocation, deallocation, and reallocation.
Enabling multiple databases to share storage cells and disks.
An Oracle Automatic Storage Management (Oracle ASM) disk group is the primary storage abstraction within Oracle ASM, and is composed of one or more grid disks.
Oracle Exadata Storage Server grid disks appear to Oracle ASM as individual disks available for membership in Oracle ASM disk groups. Whenever possible, grid disk names should correspond closely with Oracle ASM disk group names to assist in problem diagnosis between Oracle ASM and Oracle Exadata System Software.
DATA is the data disk group.
RECO is the recovery disk group.
DBFS (Oracle Database File System) is the file system disk group.
SPARSE is a sparse disk group to keep snapshot files.
To take advantage of Oracle Exadata System Software features, such as predicate processing offload, the disk groups must contain only Oracle Exadata Storage Server grid disks, and the tables must be fully inside these disk groups.
The Oracle Database and Oracle Grid Infrastructure software must be release 12.1.0.2.0 BP3 or later when using sparse grid disks.
An Oracle ASM failure group is a subset of disks in an Oracle ASM disk group that can fail together because they share the same hardware.
Oracle ASM considers failure groups when making redundancy decisions.
For Oracle Exadata Storage Servers, all grid disks, which consist of the Oracle ASM disk group members and candidates, can effectively fail together if the storage cell fails. Because of this scenario, all Oracle ASM grid disks sourced from a given storage cell should be assigned to a single failure group representing the cell.
For example, if all grid disks from two storage cells, A and B, are added to a single Oracle ASM disk group with normal redundancy, then all grid disks on storage cell A are designated as one failure group, and all grid disks on storage cell B are designated as another failure group. This enables Oracle Exadata System Software and Oracle ASM to tolerate the failure of either storage cell.
Failure groups for Oracle Exadata Storage Server grid disks are set by default so that the disks on a single cell are in the same failure group, making correct failure group configuration simple for Oracle Exadata Storage Servers.
If a cell or disk fails, then Oracle ASM automatically redistributes the cell or disk contents across the remaining disks in the disk group as long as there is enough space to hold the data. For an existing disk group using Oracle ASM redundancy, the USABLE_FILE_MB and REQUIRED_FREE_MIRROR_MB columns in the V$ASM_DISGKROUP view give the amount of usable space and space for redundancy, respectively.
If a cell or disk fails, then the remaining disks should be able to generate the IOPS necessary to sustain the performance service level agreement.
After a disk group is created, the redundancy level of the disk group cannot be changed. To change the redundancy of a disk group, you must create another disk group with the appropriate redundancy, and then move the files.
Each Exadata Cell is a failure group. A normal redundancy disk group must contain at least two failure groups. Oracle ASM automatically stores two copies of the file extents, with the mirrored extents placed in different failure groups. A high redundancy disk group must contain at least three failure groups. Oracle ASM automatically stores three copies of the file extents, with each file extent in separate failure groups.
System reliability can diminish if your environment has an insufficient number of failure groups. A small number of failure groups, or failure groups of uneven capacity, can lead to allocation problems that prevent full use of all available storage.
Oracle recommends high redundancy Oracle ASM disk groups, and file placement configuration which can be automatically deployed using Oracle Exadata Deployment Assistant. High redundancy can be configured for DATA, RECO or any other Oracle ASM group with a minimum of 3 storage cells. Starting with Exadata Software release 12.1.2.3.0, the voting disks can reside in a high redundancy disk group, and additional quorum disks (essentially equivalent to voting disks) can reside on database servers if there are fewer than 5 Exadata storage cells.
The disk groups are striped across all disks and Oracle Exadata Storage Servers to maximize I/O bandwidth and performance, and simplify management.
The DATA disk group is located on the outer section of all disks. This is true only for physical deployments. This is not applicable to Oracle VM deployments.
The RECO disk group is located on the outer/inner section of all disks. This is true only for physical deployments. This is not applicable to Oracle VM deployments.
The DBFS disk group is located on the inner section of all disks.
The DATA and RECO disk groups are configured for high redundancy.
The preceding attributes ensure optimal file placement in the different Oracle ASM disk groups. In addition, all operations have access to full I/O bandwidth, when needed. To avoid excessive resource consumption, use I/O Resource Management, Oracle Database Resource Manager, and instance caging.
Double partner disk failure: Protection against loss of the database and Oracle ASM disk group due to a disk failure followed by a second partner disk failure.
Disk failure when Oracle Exadata Storage Server is offline: Protection against loss of the database and Oracle ASM disk group when a storage server is offline and one of the storage server's partner disks fails. The storage server may be offline because of Exadata storage planned maintenance, such as Exadata rolling storage server patching.
Disk failure followed by disk sector corruption: Protection against data loss and I/O errors when latent disk sector corruptions exist and a partner storage disk is unavailable either due to planned maintenance or disk failure.
If the voting disk resides in a high redundancy disk group that is part of the default Exadata high redundancy deployment, the cluster and database will remain available for the above failure scenarios. If the voting disk resides on a normal redundancy disk group, then the database cluster will fail and the database has to be restarted. You can eliminate that risk by moving the voting disks to a high redundancy disk group and creating additional quorum disks on database servers.
Oracle recommends High Redundancy for ALL (DATA and RECO) disk groups because it provides maximum application availability against storage failures and operational simplicity during a storage outage. In contrast, if all disk groups were configured with normal redundancy and two partner disks fail, all clusters and databases on Exadata will fail and you will lose all your data (normal redundancy does not survive double partner disk failures). Other than better storage protection, the major difference between high redundancy and normal redundancy is the amount of usable storage and write I/Os. High redundancy requires more space, and has three write I/Os instead of two. The additional write I/O normally has negligible impact with Exadata smart write-back flash cache.
The following table describes that redundancy option, as well as others, and the relative availability trade-offs. The table assumes that voting disks reside in high redundancy disk group. Refer to Oracle Exadata Database Machine Maintenance Guide to migrate voting disks to high redundancy disk group for existing high redundancy disk group configurations.
Zero application downtime and zero data loss for the preceding storage outage scenarios if voting disks reside in high redundancy disk group.
If voting disks currently reside in normal redundancy disk group, refer to Oracle Exadata Database Machine Maintenance Guide to migrate them to high redundancy disk group.
Use this option for best storage protection and operational simplicity for mission-critical applications. Requires more space for higher redundancy.
Zero application downtime and zero data loss for preceding storage outage scenarios. This option requires an alternative archive destination.
New default deployment configuration with 8 TB disks.
Use this option for best storage protection for DATA with slightly higher operational complexity. More available space than High Redundancy for ALL.
Refer to My Oracle Support note 2059780.1, "Configuration Prerequisites and Operational Steps for Higher Availability for a RECO disk group or Fast Recovery Area Failure", for details.
Zero data loss for the preceding storage outage scenarios.
Note: Cross-disk mirror isolation by using ASM disk group content type limits an outage to a single disk group when two disk partners are lost in a normal redundancy group that share physical disks and storage servers.
The preceding storage outage scenarios resulted in failure of all Oracle ASM disk groups. However, using cross-disk group mirror isolation the outage is limited to one disk group.
Note: This option is not available for eighth or quarter racks.
Oracle recommends a minimum of High Redundancy for DATA only.
Use the Normal Redundancy for ALL option when the primary database is protected by an Oracle Data Guard standby database deployed on a separate Oracle Exadata Database Machine or when the Exadata Database Machine is servicing only development or test databases. Oracle Data Guard provides real-time data protection and fast failover for storage failures.
If Oracle Data Guard is not available and the DATA or RECO disk groups are lost, then leverage recovery options described in My Oracle Support note 1339373.1.
Redo log files — First high redundancy disk group. If no high redundancy disk group exists, then redo log files are multiplexed across the DATA and RECO disk groups.
Control files — First high redundancy disk group. If no high redundancy disk groups exist, the use one control file in the DATA disk group. The backup control files should reside in the RECO disk group, and RMAN CONFIGURE CONTROLFILE AUTOBACKUP ON should be set.
Server parameter files (SPFILE) — First high redundancy disk group. If no high redundancy disk group exists, then SPFILE should reside in the DATA disk group. SPFILE backups should reside in the RECO disk group.
Oracle Cluster Registry (OCR) and voting disks for Oracle Exadata Database Machine Full Rack and Oracle Exadata Database Machine Half Rack — First high redundancy disk group. If no high redundancy disk group exists, then the files should reside in the DATA disk group.
Voting disks for Oracle Exadata Database Machine Quarter Rack or Eighth Rack — First high redundancy disk group, otherwise in normal redundancy disk group. If there are fewer than 5 Exadata storage cells with high redundancy disk group, additional quorum disks will be stored on Exadata database servers during OEDA deployment. Refer to Oracle Exadata Database Machine Maintenance Guide to migrate voting disks to high redundancy disk group for existing high redundancy disk group configurations.
Temporary files — First normal redundancy disk group. If the High Redundancy for ALL option is used, then the use the first high redundancy disk group.
A grid Redundant Array of Independent Disks (RAID) configuration uses Oracle ASM mirroring capabilities. To use grid RAID, you place grid disks in an Oracle ASM disk group with a normal or high redundancy level, and set all grid disks in the same cell to be in the same Oracle ASM failure group. This ensures that Oracle ASM does not mirror data extents using disks within the cell. Using disks from different cells ensures that an individual cell failure does not cause the data to be unavailable.
Grid RAID also provides simplified creation of cell disks. With grid RAID, LUNs are automatically created from available physical disks because Oracle software automatically creates the required LUNs.
Security for Exadata Cell is enforced by identifying which clients can access cells and grid disks. Clients include Oracle ASM instances, database instances, and clusters. When creating or modifying grid disks, you can configure the Oracle ASM owner and the database clients that are allowed to use those grid disks.
In addition, the iDB protocol provides interconnection bandwidth aggregation and failover.
Cell Server (CELLSRV) services iDB requests for disk I/O and advanced Oracle Exadata Storage Server services, such as predicate processing offload. CELLSRV is implemented as a multithreaded process and should be expected to use the largest portion of processor cycles on a storage cell.
Management Server (MS) provides standalone storage cell management and configuration. MS runs on an Oracle WebLogic Server.
Restart Server (RS) monitors the CELLSRV and MS processes and restarts them, if necessary.
Each cell in the Oracle Exadata Storage Server grid is individually managed with Cell Control Command-Line Interface (CellCLI).
The CellCLI utility provides a command-line interface to the cell management functions, such as cell initial configuration, cell disk and grid disk creation, and performance monitoring. The CellCLI utility runs on the cell, and is accessible from a client computer that has network access to the storage cell or is directly connected to the cell. The CellCLI utility communicates with Management Server to administer the storage cell.
To access the cell, you should either use Secure Shell (SSH) access, or local access, for example, through a KVM switch (keyboard, video or visual display unit, mouse) switch. SSH allows remote access, but local access might be necessary during the initial configuration when the cell is not yet configured for the network. With local access, you have access to the cell operating system shell prompt and use various tools, such as the CellCLI utility, to administer the cell.
You can run the same CellCLI commands remotely on multiple cells with the dcli utility.
To manage a cell remotely from a compute node, you can use the ExaCLI utility. ExaCLI enables you to run most CellCLI commands on a cell. This is necessary if you do not have direct access to a cell to run CellCLI, or if SSH service on the cell has been disabled. To run commands on multiple cells remotely, you can use the exadcli utility.
Oracle Database instance, which contains the set of Oracle Database background processes that operate on the stored data and the shared allocated memory that those processes use to do their work.
Oracle Automatic Storage Management (Oracle ASM), which provides storage management optimized for the database and Oracle Exadata Storage Servers. Oracle ASM is part of Oracle Grid Infrastructure.
The Oracle ASM instance handles placement of data files on disks, operating as a metadata manager. The Oracle ASM instance is primarily active during file creation and extension, or during disk rebalancing following a configuration change. Run-time I/O operations are sent directly from the database to storage cells without passing through an Oracle ASM instance.
The Oracle Database Resource Manager, which ensures that I/O resources are properly allocated within a database.
The iDB protocol is used by the database instance to communicate with cells, and is implemented in an Oracle-supplied library statically linked with the database server.
Oracle Enterprise Manager 12c provides a complete target that enables you to monitor Oracle Exadata Database Machine, including configuration and performance in a graphical user interface (GUI).
The following figure shows Oracle Exadata Storage Server Home Page. Viewing this page, you can quickly see the health of the storage cells, key cell performance characteristics and resource utilization of storage by individual databases.
Description of "Figure 1-4 Oracle Exadata Storage Server Home Page in Oracle Enterprise Manager"
In addition to reports, Oracle Enterprise Manager for Oracle Exadata Storage Server enables you to set metric thresholds for alerts and monitor metric values to determine the health of a storage cell.


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Home / News/Community/
CEO: County's `Short-Term' Financial Position Good, Long-Term `Uncertain'
November 29 November 29
Karen Spiegal
Kevin Jefferies
Riverside County Board of Supervisors
(CNS) – Riverside County government's "short-term" financial position is secure thanks to expanding reserves, but the long view is "uncertain" as inflation and other potential economic drags cloud the horizon, the county's chief executive officer told the Board of Supervisors Tuesday.
"Our short-term projection is positive," CEO Jeff Van Wagenen said during a presentation on the county's First-Quarter Budget Report for 2022-23. "The medium- to long-term outlook remains uncertain at best."
The Executive Office's 22-page compendium on the first three months of the fiscal year indicated that the county is expected to end 2022-23 with an estimated reserve pool of $511 million, compared to an earlier estimate of $368 million. The county actually began the current fiscal year with over $450 million — well in excess of what officials had predicted.
EO staff attributed the larger sum to high-than-expected interest rate earnings on county investments, elevated sales tax receipts and property tax revenue.
Aggregate discretionary revenue is projected to grow to $1.076 billion, compared to $1.013 billion estimated at the beginning of 2022-23, a $63 million increase, officials said.
Discretionary income is derived from property taxes, sales and use taxes, fees charged for documents, penalties and licenses, as well earnings from the treasury's securities, mainly fixed instruments.
Inflation has driven interest rates higher.
"It's the one positive from inflation," Van Wagenen said. "But what is going to happen with inflation?"
He wondered whether cost-of-living pressures might lead to the national economy's undoing.
"There are ongoing supply chain issues and issues related to rail and other factors," Van Wagenen said. "How will that impact us going forward?"
The CEO expressed further concern over the California Public Employees' Retirement System, CalPERS, going "upside-down" on its investment portfolio, losing ground that it had gained in recent years.
Supervisor Kevin Jeffries, a strong pension reform advocate, urged the Executive Office to think ahead and plan for the inevitable backfill that will be required to cover the county's portion of the retirement system's losses.
"I hope we will exercise restraint on our expenses," Jeffries said. "Otherwise, it could come back to haunt us."
Supervisor Karen Spiegel supported preserving the reserve pool to whatever extent possible because it is "prudent … to set aside (funds) for that rainy day."
"We know the market is going to dip," she said. "I hope that departments understand … we have this money set aside for a little relief. We're looking at how to level things out. But there has got to be an end to that bucket."
Board Chairman Jeff Hewitt said the state's financial position manifested instability that would affect the county going into the next budget cycle.
"Last year, they had a $100 billion surplus," Hewitt said. "This year, they're projecting a $25 billion deficit."
Van Wagenen acknowledged the negative aspects and said the process of engaging the county's 40-plus departments "to determine the ripple effect of the state budget losses" was already underway.
The county's midyear budget report will cover the array of challenges heading into 2023-24. That hearing is tentatively set for Feb. 28.
In June, the board approved a $7.45 billion budget for 2022-23, roughly 8% larger than the 2021-22 budget of $6.88 billion. The bulk of that money is comprised of non-discretionary, or programmed, budget appropriations and includes "pass-through" revenue streams from the state and federal governments.
The county received almost $500 million in 2020 Coronavirus Aid, Relief & Economic Security Act allocations and another $480 million in 2021 American Rescue Plan Act money, and Van Wagenen acknowledged in June that just under 10% of the federal infusions were being applied to "budget stabilization" in 2022-23.
The funds have been used for homeless and rental assistance programs, along with other social welfare efforts, but they've also been appropriated for multiple infrastructure, or capital improvement, projects.


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Langenbecks Arch Surg October; 5: Nowadays, there exists a large quantity of many times contradictory scientific information. The authors used PICO to describe all the components related to the identified problem and to structure the research question, which was: Having access to the knowledge produced about a certain subject is essential for the development of good research and adequate clinical action.
English Portuguese Copyright of Revista Medicina is the property of Revista Medicina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission.
Principles of evidence based medicine. These four components are the essential elements of the research question in EBP and of the construction of the question for the bibliographic search of evidence 7, Archie Cochrane United Kingdom exerted a profound influence on the assessment of medical interventions, establishing the importance of RCT in the evaluation of treatment effectiveness 5.
Once the research question is formulated, the following stage is the beginning of the bibliographic search for evidence, which allows for the recovery of evidence in the databases, and can be schematized in the following stagesWhen analyzing the dressings available, they detected that modern dressings possess silver in their composition anti-microbial but are not widely used. Today, there are several clinical trials available in the databases.
This abstract may be abridged. Rev Latino-am Enfermagem maio-junho;13 3: Int J Nurs Pract December;7 6: Evidence based practice is the use of the best scientific evidence to support the clinical decision making.
It is also very easy to access studies developed all over the world. The PICO strategy helps in these definitions, because it orients eestrategia construction of the research question and of the bibliographic search, and permits clinical and research professional, in case of doubt or questioning, to rapidly and accurately locate the best scientific information available.
EBP aims to improve care through the identification and promotion of workable practices and, at the same time, through the elimination of inefficient and prejudicial ones 7minimizing the gap between the generation of evidence and its application in patient care.
All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License. The EBP previews methodologies and processes in order to identify evidence of whether a certain treatment or diagnosis is effective, strategies to evaluate the quality of studies and mechanisms to implement it in care.
Selection of the search terms: Remote access to EBSCO's databases is permitted to patrons of subscribing institutions accessing from remote locations for personal, non-commercial use. Emerg Med J July;19 4: What is evidence-based medicine? Bergin SM, Wraight P. For this reason, it is essential that every researcher is familiarized with strategies to develop a research question, as each one of its components must be defined. In this review a description of the characteristics of a good research question and its construction by the strategy known as PICOT will be made.
Systematic review represents the use of a standardized method to synthesize data from multiple primary studies 8. Use of Boolean operators: Such final strategy must be inserted in the search box existent in the databases, so that evidence is located by means of a bibliographic search. However, users may print, download, or email articles for individual use.
Services on Demand Journal. Identifying the research question and planning the project. In addition, this paper provides a description of possible epidemiological oicot that can be derived from this question, its advantages and disadvantages.
This information will be important for the correct application of evidence-based medicine. The descriptors are classified as: In the course of the twentieth century, health research techniques have been refined and clinical trials have improved.
Arch Dis Child August;90 8: The results obtained through such reviews are biased, do not exhaust all the literature available about the theme and are usually inconclusive.
Data from the systematic review by Bergin and Wraight 16 are used to exemplify the construction of the research question using the PICO strategy. Number and size of randomized trials reported in general health care journals from to RCT studies have showed conflicting results in situations with similar research objectives and objects and generate doubts regarding effectiveness, fundamentation, indications and results of several health practices.
How to cite this article. Table 2 presents the four components of the PICO strategy and Table 3 presents an example of its use to construct a research question 13, Users should refer to the original published version of the material for the full abstract.


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Growing role for city farms
FEBRUARY 7, 2008: The important role of city farms and community gardens is increasinglyrecognised by local and national government, funders and otherstakeholders, according to a report.
The Federation of City Farms and Community Gardens aims to support, represent and promote community-managed farms and gardens.In a report on the past year, director Jeremey Iles and chair David Drury said: "The number of city farms has remained constant – reflecting the difficulties in obtaining funds and land to develop new projects – while there has been an upsurge in interest in communitry gardens, allotmemnts and school farms."Meanwhile, the growing National Care Farming Initiative has recognised the excellent work done in this area by pioneering city farms."The Federation was instrumental in helping develop the £50m Local Food programme and £50m Community Spaces programme."We are currently developing five year strategies for England, Northern Ireland, Scotland, Wales and London in consultation with our members and partners."* More: www.farmgarden.org.uk
by Country Smallholding


If Kate Beckinsale wants a foreskin facial I'm prepared to step up to the plate. Sandra Bullock, not so much.
It's nice that Koreans have found market value in their unwanted foreskins. Waste not want not, that's what I say.


Our downhill race on the weekend up on the hill was a fantastic weekend… a record 298 entries!
A huge hearty congratulations to Ben Annear for doing so much work to make it a such a success!
Thanks also to the VDHS committee for allowing us to host the event.
And an absolutely HUGE thank you to all our members who volunteered their time, be it course setting, car parking, course marshalling… whatever.
Thank you to: Elise Empey, Matt Empey, Dan Friday, Dave Empey, Peter Ellett, Steve Duke, Judi Duke, Tim Hall, Bruce Halket, Kate Stonnill, Tim Ross and Jason Parker.
Another even bigger thank you to the following who volunteered for BOTH days of the event: Adam Baker, Allan Gerrans and Richard Plumb.
Finally, a massive thank you to the following who volunteered even though they're not even members!
Andy (coty) Setchell, Craig Kappes, Peter Coffey, Nikki Coffey, Caleb Stoneman, Reece Stephenson, Gemma Ferguson, Nick Ferguson, Vickie Vanderhoeven, Jackson Vanderhoeven and Ariel Stava.
If you don't already have one, there's an MMBCC t-shirt coming your way!
Shannon Rademaker finished 4th in Vets, Dan Friday 3rd in Short Travel class, Elise Empey finished in 4th (just .03 secs off third) and an awesome 9th (top ten!) to Maddie Smith in Women.
We're thrilled to announce that Dion Theodossi and his team at Martins Garage are the new Naming Rights Sponsor of our tour - the Mansfield Subaru Tour!
Plus we can also confirm that All Terrain Cycles are back on-board to sponsor the Sprint prizes.
But wait… there's more! Torq nutrition are sponsoring too!
And we'll be able to announce at least one more sponsor shortly.
We're really excited that it's going to be a great event. So, please contact Wil to let him know which job you'd like to volunteer for.
An Individual Time Trial (ITT) is usually known as the 'race of truth' - there's no where to hide in a bunch and no wheel to follow. Just each rider, alone, against the clock.
It's usually accompanied by aerodynamic enhancements such as time trial handlebar extensions, skin suits and aero helmets.
However, the ITT held by the Mansfield Mt Buller Cycling Club on Thursday 17 January was the Rob Curtis Memorial Hillclimb - held on a course which kept speeds so slow that being 'aero' was virtually irrelevant. While it was only a relatively short 10km, it was all uphill.
There is a suspicion that the Uphill time trial was the brainchild of Thursday Night Race Director Di Condie; who planned a 10km dose of pain because she knew she'd be away on holidays, watching the Tour Down Under in Adelaide. Thanks Di!
On a very warm evening 12 year old Oscar Hall, visiting from Benalla, started things off. With so many away on holiday, or out fighting fires, or worried about the heat, he was followed by only another 11 riders at 30 second intervals.
Even though Damian Grundy was the first across the line, followed by Oscar's Dad Simon, it was Oscar who took the win with a time of 34.59, corrected to 19.59 on handicap.
John Lazarov continued his transformation into a climber to take second in 20.28 with Judi Duke third in 20.44, ahead of the two Hall brothers, Simon and Tim.
Bruce Halket rode fastest time in 25.22.
During presentations back at the Delatite Hotel, Club President Damian Grundy announced that all entry monies would be donated to the Red Cross in Rob Curtis' name.
Next week is everyone's favourite, a 32km Handicap from the Botanic Park, up to Sawpit Gully Road and around the Barwite Loop to Graves Road. Entries via SMS the usual way by 8pm Wednesday.
Many thanks to all our officials and volunteers. Here are the results and thanks to Tony Copland for the pics.
It's that time of year for Cycling Australia (road) memberships… again!
If you haven't already, please make sure you renew before you enter your next race. Here's the link you need to renew your membership so you can race in 2019.
However, not unusually, there seems to be some kind of admin glitch at CA. A few members have renewed but their name doesn't yet appear on the CA membership list that we download. So please bring your renewal receipt with you to the next race to prove that you have a valid 2019 race licence.
Remember, no membership - no race!
Road racing continues this Thursday with a 32km Handicap from the Botanic Park, up to Sawpit Gully Road and then around to Graves Road (course 6). Please check the duty roster.
Dirt Crits is still a few weeks away, starting again on Tuesday 5 February. Here's the calendar.
An interesting article on road cycling in the 'mainstream' media. Victoria needs to lift its game.


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Asheville Citizen-Times
John W. Parker
Share John's life story with friends and family
Asheville - John W. Parker, 91, died Wednesday, October 28, 2015.
A native of Mars Hill, Mr. Parker was a son of the late William Cleveland Parker and Bessie Robinson Parker. He was married to Betty June Miller Parker, who died in January, 2014, and was also preceded in death by a grandson, George Thomas Parker, Jr.
Mr. Parker was a Navy veteran of WW II and was retired from the US Postal Service. He was a member of West Asheville Baptist Church, the Young at Heart Group, the Asheville Boat and Ski Club, the Asheville Bowling League and was a former member of the Royal Arcanum and the Good Fellowship Club.
He is survived by his sons, George Thomas "Tom" Parker and his wife, Carol, and John David "Dave" Parker and his wife, Barbara; grandchildren, Renee Skiles and her husband, Tom, and Captain Jon David Parker, USMC; great-grandchildren, Amanda Lee, Lauren and Tommy Skiles; and a sister, Bonnie Towe.
Funeral services will be at 1:00 p.m. Saturday in the Patton Avenue chapel of Groce Funeral Home with the Rev. Dr. Stan Welch officiating. Interment with military honors will follow at Green Hills Cemetery.
The family will receive friends at the funeral home one hour prior to the service.
The family wishes to express special appreciation to the staff of Arbor Terrace Memory Care Unit for the loving care they provided for Mr. Parker.
Memorials may be made to West Asheville Baptist Church, 926 Haywood Road, Asheville, NC 28806.
The online register is available at www.grocefuneralhome.com.
Published in Asheville Citizen-Times on Oct. 30, 2015.
Groce Funeral Home
1401 Patton Avenue
4 Guys Having Fun on Leave
I just read about Johnny Parker's passing away and I am very sorry to hear that. My condolences to the family. We were best friends serving on the USS Penelope. Dr. John and Gloria Felice
John Felice
Find comfort in the God who is close to the brokenhearted.
Dear Family, l pray for and with you, as you Bless the Lord for such a Great Man.
Rev. James Grant
Tom, So sorry to hear of the passing of your father. Remembering you in our thoughts and prayers.
Karen & Maurice Gortney
Our sympathy to the parker family in the loss of john.he was a best friend since childhood to our deceased father R.G.Moss.he and june were also good friends to our deceased mother, Pat Moss.he will be missed. Gods peace to your family at this time. Ken, Steve Moss and Lynda Moss Alexander.
John was a special neighbor & will be missed.
Bo Hobson