Seems like seq2sparse would be really easy to replace since it takes text files to start with, then the whole pipeline could be kept in rdds. The dictionaries and counts could be either in-memory maps or rdds for use with joins? This would get rid of sequence files completely from the pipeline. Item similarity uses in-memory maps but the plan is to make it more scalable using joins as an alternative with the same API allowing the user to trade-off footprint for speed.
My use for TF-IDF is for row similarity and would take a DRM (actually IndexedDataset) and calculate row/doc similarities. It works now but only using LLR. This is OK when thinking of the items as tags or metadata but for text tokens something like cosine may be better. I’d imagine a downsampling phase that would precede TF-IDF using LLR a lot like how CF preferences are downsampled. This would produce an sparsified all-docs DRM. Then (if the counts were saved) TF-IDF would re-weight the terms before row similarity uses cosine. This is not so good for search but should produce much better similarities than Solr’s “moreLikeThis” and does it for all pairs rather than one at a time. In any case it can be used to do a create a personalized content-based recommender or augment a CF recommender with one more indicator type. On Feb 3, 2015, at 3:37 PM, Andrew Palumbo <ap....@outlook.com> wrote: On 02/03/2015 12:44 PM, Andrew Palumbo wrote: > > On 02/03/2015 12:22 PM, Pat Ferrel wrote: >> Some issues WRT lower level Spark integration: >> 1) interoperability with Spark data. TF-IDF is one example I actually looked >> at. There may be other things we can pick up from their committers since >> they have an abundance. >> 2) wider acceptance of Mahout DSL. The DSL’s power was illustrated to me >> when someone on the Spark list asked about matrix transpose and an MLlib >> committer’s answer was something like “why would you want to do that?”. >> Usually you don’t actually execute the transpose but they don’t even support >> A’A, AA’, or A’B, which are core to what I work on. At present you pretty >> much have to choose between MLlib or Mahout for sparse matrix stuff. Maybe a >> half-way measure is some implicit conversions (ugh, I know). If the DSL >> could interchange datasets with MLlib, people would be pointed to the DSL >> for all of a bunch of “why would you want to do that?” features. MLlib seems >> to be algorithms, not math. >> 3) integration of Streaming. DStreams support most of the RDD interface. >> Doing a batch recalc on a moving time window would nearly fall out of >> DStream backed DRMs. This isn’t the same as incremental updates on streaming >> but it’s a start. >> >> Last year we were looking at Hadoop Mapreduce vs Spark, H2O, Flink faster >> compute engines. So we jumped. Now the need is for streaming and especially >> incrementally updated streaming. Seems like we need to address this. >> >> Andrew, regardless of the above having TF-IDF would be super helpful—row >> similarity for content/text would benefit greatly. > > I will put a PR up soon. Just to clarify, I'll be porting over the (very simple) TF, TFIDF classes and Weight interface over from mr-legacy to math-scala. They're available now in spark-shell but won't be after this refactoring. These still require dictionary and a frequency count maps to vectorize incoming text- so they're more for use with the old MR seq2sparse and I don't think they can be used with Spark's HashingTF and IDF. I'll put them up soon. Hopefully they'll be of some use. On Feb 3, 2015, at 8:47 AM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: >> >> But first I need to do massive fixes and improvements to the distributed >> optimizer itself. Still waiting on green light for that. >> On Feb 3, 2015 8:45 AM, "Dmitriy Lyubimov" <dlie...@gmail.com> wrote: >> >>> On Feb 3, 2015 7:20 AM, "Pat Ferrel" <p...@occamsmachete.com> wrote: >>>> BTW what level of difficulty would making the DSL run on MLlib Vectors >>> and RowMatrix be? Looking at using their hashing TF-IDF but it raises >>> impedance mismatch between DRM and MLlib RowMatrix. This would further >>> reduce artifact size by a bunch. >>> >>> Short answer, if it were possible, I'd not bother with Mahout code base at >>> all. The problem is it lacks sufficient flexibility semantics and >>> abstruction. Breeze is indefinitely better in that department but at the >>> time it was sufficiently worse on abstracting interoperability of matrices >>> with different structures. And mllib does not expose breeze. >>> >>> Looking forward toward hardware acellerated bolt-on work I just must say >>> after reading breeze code for some time I still have much clearer plan how >>> such back hybridization and cost calibration might work with current Mahout >>> math abstractions than with breeze. It is also more in line with my current >>> work tasks. >>> >>>> Also backing something like a DRM with DStreams. Periodic model recalc >>> with streams is maybe the first step towards truly streaming algos. Looking >>> at DStream -> DRM conversion for A’A, A’B, and AA’ in item and row >>> similarity. Attach Kafka and get evergreen models, if not incrementally >>> updating models. >>>> On Feb 2, 2015, at 4:54 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: >>>> >>>> bottom line compile-time dependencies are satisfied with no extra stuff >>>> from mr-legacy or its transitives. This is proven by virtue of >>> successful >>>> compilation with no dependency on mr-legacy on the tree. >>>> >>>> Runtime sufficiency for no extra dependency is proven via running shell >>> or >>>> embedded tests (unit tests) which are successful too. This implies >>>> embedding and shell apis. >>>> >>>> Issue with guava is typical one. if it were an issue, i wouldn't be able >>> to >>>> compile and/or run stuff. Now, question is what do we do if drivers want >>>> extra stuff that is not found in Spark. >>>> >>>> Now, It is so nice not to depend on anything extra so i am hesitant to >>>> offer anything here. either shading or lib with opt-in dependency policy >>>> would suffice though, since it doesn't look like we'd have to have tons >>> of >>>> extra for drivers. >>>> >>>> >>>> >>>> On Sat, Jan 31, 2015 at 10:17 AM, Pat Ferrel <p...@occamsmachete.com> >>> wrote: >>>>> I vaguely remember there being a Guava version problem where the >>> version >>>>> had to be rolled back in one of the hadoop modules. The math-scala >>>>> IndexedDataset shouldn’t care about version. >>>>> >>>>> BTW It seems pretty easy to take out the option parser and replace with >>>>> match and tuples especially if we can extend the Scala App class. It >>> might >>>>> actually simplify things since I can then use several case classes to >>> hold >>>>> options (scopt needed one object), which in turn takes out all those >>> ugly >>>>> casts. I’ll take a look next time I’m in there. >>>>> >>>>> On Jan 30, 2015, at 4:07 PM, Dmitriy Lyubimov <dlie...@gmail.com> >>> wrote: >>>>> in 'spark' module it is overwritten with spark dependency, which also >>> comes >>>>> at the same version so happens. so should be fine with 1.1.x >>>>> >>>>> [INFO] --- maven-dependency-plugin:2.8:tree (default-cli) @ >>>>> mahout-spark_2.10 --- >>>>> [INFO] org.apache.mahout:mahout-spark_2.10:jar:1.0-SNAPSHOT >>>>> [INFO] +- org.apache.spark:spark-core_2.10:jar:1.1.0:compile >>>>> [INFO] | +- org.apache.hadoop:hadoop-client:jar:2.2.0:compile >>>>> [INFO] | | +- org.apache.hadoop:hadoop-common:jar:2.2.0:compile >>>>> [INFO] | | | +- commons-cli:commons-cli:jar:1.2:compile >>>>> [INFO] | | | +- org.apache.commons:commons-math:jar:2.1:compile >>>>> [INFO] | | | +- commons-io:commons-io:jar:2.4:compile >>>>> [INFO] | | | +- commons-logging:commons-logging:jar:1.1.3:compile >>>>> [INFO] | | | +- commons-lang:commons-lang:jar:2.6:compile >>>>> [INFO] | | | +- >>>>> commons-configuration:commons-configuration:jar:1.6:compile >>>>> [INFO] | | | | +- >>>>> commons-collections:commons-collections:jar:3.2.1:compile >>>>> [INFO] | | | | +- commons-digester:commons-digester:jar:1.8:compile >>>>> [INFO] | | | | | \- >>>>> commons-beanutils:commons-beanutils:jar:1.7.0:compile >>>>> [INFO] | | | | \- >>>>> commons-beanutils:commons-beanutils-core:jar:1.8.0:compile >>>>> [INFO] | | | +- org.apache.avro:avro:jar:1.7.4:compile >>>>> [INFO] | | | +- com.google.protobuf:protobuf-java:jar:2.5.0:compile >>>>> [INFO] | | | +- org.apache.hadoop:hadoop-auth:jar:2.2.0:compile >>>>> [INFO] | | | \- >>> org.apache.commons:commons-compress:jar:1.4.1:compile >>>>> [INFO] | | | \- org.tukaani:xz:jar:1.0:compile >>>>> [INFO] | | +- org.apache.hadoop:hadoop-hdfs:jar:2.2.0:compile >>>>> [INFO] | | +- >>>>> org.apache.hadoop:hadoop-mapreduce-client-app:jar:2.2.0:compile >>>>> [INFO] | | | +- >>>>> org.apache.hadoop:hadoop-mapreduce-client-common:jar:2.2.0:compile >>>>> [INFO] | | | | +- >>>>> org.apache.hadoop:hadoop-yarn-client:jar:2.2.0:compile >>>>> [INFO] | | | | | +- com.google.inject:guice:jar:3.0:compile >>>>> [INFO] | | | | | | +- javax.inject:javax.inject:jar:1:compile >>>>> [INFO] | | | | | | \- aopalliance:aopalliance:jar:1.0:compile >>>>> [INFO] | | | | | +- >>>>> >>>>> >>> com.sun.jersey.jersey-test-framework:jersey-test-framework-grizzly2:jar:1.9:compile >>> >>>>> [INFO] | | | | | | +- >>>>> >>>>> >>> com.sun.jersey.jersey-test-framework:jersey-test-framework-core:jar:1.9:compile >>> >>>>> [INFO] | | | | | | | +- >>>>> javax.servlet:javax.servlet-api:jar:3.0.1:compile >>>>> [INFO] | | | | | | | \- >>> com.sun.jersey:jersey-client:jar:1.9:compile >>>>> [INFO] | | | | | | \- >>> com.sun.jersey:jersey-grizzly2:jar:1.9:compile >>>>> [INFO] | | | | | | +- >>>>> org.glassfish.grizzly:grizzly-http:jar:2.1.2:compile >>>>> [INFO] | | | | | | | \- >>>>> org.glassfish.grizzly:grizzly-framework:jar:2.1.2:compile >>>>> [INFO] | | | | | | | \- >>>>> org.glassfish.gmbal:gmbal-api-only:jar:3.0.0-b023:compile >>>>> [INFO] | | | | | | | \- >>>>> org.glassfish.external:management-api:jar:3.0.0-b012:compile >>>>> [INFO] | | | | | | +- >>>>> org.glassfish.grizzly:grizzly-http-server:jar:2.1.2:compile >>>>> [INFO] | | | | | | | \- >>>>> org.glassfish.grizzly:grizzly-rcm:jar:2.1.2:compile >>>>> [INFO] | | | | | | +- >>>>> org.glassfish.grizzly:grizzly-http-servlet:jar:2.1.2:compile >>>>> [INFO] | | | | | | \- >>> org.glassfish:javax.servlet:jar:3.1:compile >>>>> [INFO] | | | | | +- com.sun.jersey:jersey-server:jar:1.9:compile >>>>> [INFO] | | | | | | +- asm:asm:jar:3.1:compile >>>>> [INFO] | | | | | | \- com.sun.jersey:jersey-core:jar:1.9:compile >>>>> [INFO] | | | | | +- com.sun.jersey:jersey-json:jar:1.9:compile >>>>> [INFO] | | | | | | +- >>> org.codehaus.jettison:jettison:jar:1.1:compile >>>>> [INFO] | | | | | | | \- stax:stax-api:jar:1.0.1:compile >>>>> [INFO] | | | | | | +- >>> com.sun.xml.bind:jaxb-impl:jar:2.2.3-1:compile >>>>> [INFO] | | | | | | | \- >>> javax.xml.bind:jaxb-api:jar:2.2.2:compile >>>>> [INFO] | | | | | | | \- >>>>> javax.activation:activation:jar:1.1:compile >>>>> [INFO] | | | | | | +- >>>>> org.codehaus.jackson:jackson-jaxrs:jar:1.8.3:compile >>>>> [INFO] | | | | | | \- >>>>> org.codehaus.jackson:jackson-xc:jar:1.8.3:compile >>>>> [INFO] | | | | | \- >>>>> com.sun.jersey.contribs:jersey-guice:jar:1.9:compile >>>>> [INFO] | | | | \- >>>>> org.apache.hadoop:hadoop-yarn-server-common:jar:2.2.0:compile >>>>> [INFO] | | | \- >>>>> org.apache.hadoop:hadoop-mapreduce-client-shuffle:jar:2.2.0:compile >>>>> [INFO] | | +- org.apache.hadoop:hadoop-yarn-api:jar:2.2.0:compile >>>>> [INFO] | | +- >>>>> org.apache.hadoop:hadoop-mapreduce-client-core:jar:2.2.0:compile >>>>> [INFO] | | | \- >>> org.apache.hadoop:hadoop-yarn-common:jar:2.2.0:compile >>>>> [INFO] | | +- >>>>> org.apache.hadoop:hadoop-mapreduce-client-jobclient:jar:2.2.0:compile >>>>> [INFO] | | \- org.apache.hadoop:hadoop-annotations:jar:2.2.0:compile >>>>> [INFO] | +- net.java.dev.jets3t:jets3t:jar:0.7.1:compile >>>>> [INFO] | | +- commons-codec:commons-codec:jar:1.3:compile >>>>> [INFO] | | \- commons-httpclient:commons-httpclient:jar:3.1:compile >>>>> [INFO] | +- org.apache.curator:curator-recipes:jar:2.4.0:compile >>>>> [INFO] | | +- org.apache.curator:curator-framework:jar:2.4.0:compile >>>>> [INFO] | | | \- org.apache.curator:curator-client:jar:2.4.0:compile >>>>> [INFO] | | \- org.apache.zookeeper:zookeeper:jar:3.4.5:compile >>>>> [INFO] | | \- jline:jline:jar:0.9.94:compile >>>>> [INFO] | +- org.eclipse.jetty:jetty-plus:jar:8.1.14.v20131031:compile >>>>> [INFO] | | +- >>>>> >>> org.eclipse.jetty.orbit:javax.transaction:jar:1.1.1.v201105210645:compile >>>>> [INFO] | | +- >>> org.eclipse.jetty:jetty-webapp:jar:8.1.14.v20131031:compile >>>>> [INFO] | | | +- >>> org.eclipse.jetty:jetty-xml:jar:8.1.14.v20131031:compile >>>>> [INFO] | | | \- >>>>> org.eclipse.jetty:jetty-servlet:jar:8.1.14.v20131031:compile >>>>> [INFO] | | \- >>> org.eclipse.jetty:jetty-jndi:jar:8.1.14.v20131031:compile >>>>> [INFO] | | \- >>>>> >>>>> >>> org.eclipse.jetty.orbit:javax.mail.glassfish:jar:1.4.1.v201005082020:compile >>> >>>>> [INFO] | | \- >>>>> >>> org.eclipse.jetty.orbit:javax.activation:jar:1.1.0.v201105071233:compile >>>>> [INFO] | +- >>> org.eclipse.jetty:jetty-security:jar:8.1.14.v20131031:compile >>>>> [INFO] | +- org.eclipse.jetty:jetty-util:jar:8.1.14.v20131031:compile >>>>> [INFO] | +- >>> org.eclipse.jetty:jetty-server:jar:8.1.14.v20131031:compile >>>>> [INFO] | | +- >>>>> org.eclipse.jetty.orbit:javax.servlet:jar:3.0.0.v201112011016:compile >>>>> [INFO] | | +- >>>>> org.eclipse.jetty:jetty-continuation:jar:8.1.14.v20131031:compile >>>>> [INFO] | | \- >>> org.eclipse.jetty:jetty-http:jar:8.1.14.v20131031:compile >>>>> [INFO] | | \- >>> org.eclipse.jetty:jetty-io:jar:8.1.14.v20131031:compile >>>>> [INFO] | +- com.google.guava:guava:jar:16.0:compile >>>>> d >>>>> >>>>> On Fri, Jan 30, 2015 at 4:03 PM, Dmitriy Lyubimov <dlie...@gmail.com> >>>>> wrote: >>>>> >>>>>> looks like it is also requested by mahout-math, wonder what is using >>> it >>>>>> there. >>>>>> >>>>>> At very least, it needs to be synchronized to the one currently used >>> by >>>>>> spark. >>>>>> >>>>>> [INFO] --- maven-dependency-plugin:2.8:tree (default-cli) @ >>> mahout-hadoop >>>>>> --- >>>>>> [INFO] org.apache.mahout:mahout-hadoop:jar:1.0-SNAPSHOT >>>>>> *[INFO] +- org.apache.mahout:mahout-math:jar:1.0-SNAPSHOT:compile* >>>>>> [INFO] | +- org.apache.commons:commons-math3:jar:3.2:compile >>>>>> *[INFO] | +- com.google.guava:guava:jar:16.0:compile* >>>>>> [INFO] | \- com.tdunning:t-digest:jar:2.0.2:compile >>>>>> [INFO] +- >>> org.apache.mahout:mahout-math:test-jar:tests:1.0-SNAPSHOT:test >>>>>> [INFO] +- org.apache.hadoop:hadoop-client:jar:2.2.0:compile >>>>>> [INFO] | +- org.apache.hadoop:hadoop-common:jar:2.2.0:compile >>>>>> >>>>>> >>>>>> On Fri, Jan 30, 2015 at 7:52 AM, Pat Ferrel <p...@occamsmachete.com> >>>>> wrote: >>>>>>> Looks like Guava is in Spark. >>>>>>> >>>>>>> On Jan 29, 2015, at 4:03 PM, Pat Ferrel <p...@occamsmachete.com> >>> wrote: >>>>>>> IndexedDataset uses Guava. Can’t tell from sure but it sounds like >>> this >>>>>>> would not be included since I think it was taken from the mrlegacy >>> jar. >>>>>>> On Jan 25, 2015, at 10:52 AM, Dmitriy Lyubimov <dlie...@gmail.com> >>>>> wrote: >>>>>>> ---------- Forwarded message ---------- >>>>>>> From: "Pat Ferrel" <p...@occamsmachete.com> >>>>>>> Date: Jan 25, 2015 9:39 AM >>>>>>> Subject: Re: Codebase refactoring proposal >>>>>>> To: <dev@mahout.apache.org> >>>>>>> Cc: >>>>>>> >>>>>>>> When you get a chance a PR would be good. >>>>>>> Yes, it would. And not just for that. >>>>>>> >>>>>>>> As I understand it you are putting some class jars somewhere in the >>>>>>> classpath. Where? How? >>>>>>> /bin/mahout >>>>>>> >>>>>>> (Computes 2 different classpaths. See 'bin/mahout classpath' vs. >>>>>>> 'bin/mahout -spark'.) >>>>>>> >>>>>>> If i interpret current shell code there correctky, legacy path tries >>> to >>>>>>> use >>>>>>> examples assemblies if not packaged, or /lib if packaged. True >>>>> motivation >>>>>>> of that significantly predates 2010 and i suspect only Benson knows >>>>> whole >>>>>>> true intent there. >>>>>>> >>>>>>> The spark path, which is really a quick hack of the script, tries to >>> get >>>>>>> only selected mahout jars and locally instlalled spark classpath >>> which i >>>>>>> guess is just the shaded spark jar in recent spark releases. It also >>>>>>> apparently tries to include /libs/*, which is never compiled in >>>>> unpackaged >>>>>>> version, and now i think it is a bug it is included because /libs/* >>> is >>>>>>> apparently legacy packaging, and shouldnt be used in spark jobs >>> with a >>>>>>> wildcard. I cant beleive how lazy i am, i still did not find time to >>>>>>> understand mahout build in all cases. >>>>>>> >>>>>>> I am not even sure if packaged mahout will work with spark, honestly, >>>>>>> because of the /lib. Never tried that, since i mostly use application >>>>>>> embedding techniques. >>>>>>> >>>>>>> The same solution may apply to adding external dependencies and >>> removing >>>>>>> the assembly in the Spark module. Which would leave only one major >>> build >>>>>>> issue afaik. >>>>>>>> On Jan 24, 2015, at 11:53 PM, Dmitriy Lyubimov <dlie...@gmail.com> >>>>>>> wrote: >>>>>>>> No, no PR. Only experiment on private. But i believe i sufficiently >>>>>>> defined >>>>>>>> what i want to do in order to gauge if we may want to advance it >>> some >>>>>>> time >>>>>>>> later. Goal is much lighter dependency for spark code. Eliminate >>>>>>> everything >>>>>>>> that is not compile-time dependent. (and a lot of it is thru legacy >>> MR >>>>>>> code >>>>>>>> which we of course don't use). >>>>>>>> >>>>>>>> Cant say i understand the remaining issues you are talking about >>>>> though. >>>>>>>> If you are talking about compiling lib or shaded assembly, no, this >>>>>>> doesn't >>>>>>>> do anything about it. Although point is, as it stands, the algebra >>> and >>>>>>>> shell don't have any external dependencies but spark and these 4 >>> (5?) >>>>>>>> mahout jars so they technically don't even need an assembly (as >>>>>>>> demonstrated). >>>>>>>> >>>>>>>> As i said, it seems driver code is the only one that may need some >>>>>>> external >>>>>>>> dependencies, but that's a different scenario from those i am >>> talking >>>>>>>> about. But i am relatively happy with having the first two working >>>>>>> nicely >>>>>>>> at this point. >>>>>>>> >>>>>>>> On Sat, Jan 24, 2015 at 9:06 AM, Pat Ferrel <p...@occamsmachete.com> >>>>>>> wrote: >>>>>>>>> +1 >>>>>>>>> >>>>>>>>> Is there a PR? You mention a "tiny mahout-hadoop” module. It would >>> be >>>>>>> nice >>>>>>>>> to see how you’ve structured that in case we can use the same >>> model to >>>>>>>>> solve the two remaining refactoring issues. >>>>>>>>> 1) external dependencies in the spark module >>>>>>>>> 2) no spark or h2o in the release artifacts. >>>>>>>>> >>>>>>>>> On Jan 23, 2015, at 6:45 PM, Shannon Quinn <squ...@gatech.edu> >>> wrote: >>>>>>>>> Also +1 >>>>>>>>> >>>>>>>>> iPhone'd >>>>>>>>> >>>>>>>>>> On Jan 23, 2015, at 18:38, Andrew Palumbo <ap....@outlook.com> >>>>> wrote: >>>>>>>>>> +1 >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> Sent from my Verizon Wireless 4G LTE smartphone >>>>>>>>>> >>>>>>>>>> <div>-------- Original message --------</div><div>From: Dmitriy >>>>>>> Lyubimov >>>>>>>>> <dlie...@gmail.com> </div><div>Date:01/23/2015 6:06 PM >>> (GMT-05:00) >>>>>>>>> </div><div>To: dev@mahout.apache.org </div><div>Subject: Codebase >>>>>>>>> refactoring proposal </div><div> >>>>>>>>>> </div> >>>>>>>>>> So right now mahout-spark depends on mr-legacy. >>>>>>>>>> I did quick refactoring and it turns out it only _irrevocably_ >>>>> depends >>>>>>> on >>>>>>>>>> the following classes there: >>>>>>>>>> >>>>>>>>>> MatrixWritable, VectorWritable, Varint/Varlong and VarintWritable, >>>>> and >>>>>>>>> ... >>>>>>>>>> *sigh* o.a.m.common.Pair >>>>>>>>>> >>>>>>>>>> So I just dropped those five classes into new a new tiny >>>>>>> mahout-hadoop >>>>>>>>>> module (to signify stuff that is directly relevant to serializing >>>>>>> thigns >>>>>>>>> to >>>>>>>>>> DFS API) and completely removed mrlegacy and its transients from >>>>> spark >>>>>>>>> and >>>>>>>>>> spark-shell dependencies. >>>>>>>>>> >>>>>>>>>> So non-cli applications (shell scripts and embedded api use) >>> actually >>>>>>>>> only >>>>>>>>>> need spark dependencies (which come from SPARK_HOME classpath, of >>>>>>> course) >>>>>>>>>> and mahout jars (mahout-spark, mahout-math(-scala), mahout-hadoop >>> and >>>>>>>>>> optionally mahout-spark-shell (for running shell)). >>>>>>>>>> >>>>>>>>>> This of course still doesn't address driver problems that want to >>>>>>> throw >>>>>>>>>> more stuff into front-end classpath (such as cli parser) but at >>> least >>>>>>> it >>>>>>>>>> renders transitive luggage of mr-legacy (and the size of >>>>>>> worker-shipped >>>>>>>>>> jars) much more tolerable. >>>>>>>>>> >>>>>>>>>> How does that sound? >>>>>>>>> >>>>>>> >>>>>>> >>>>> >
